# Contributions to the Optimization of Wireless Broadcast/Broadband Systems: Differentiated and Convergent Approaches

Matthieu Crussière

► To cite this version:

Matthieu Crussière. Contributions to the Optimization of Wireless Broadcast/Broadband Systems: Differentiated and Convergent Approaches. Engineering Sciences [physics]. Université de rennes 1, 2017. tel-04361987

HAL Id: tel-04361987

https://hal.science/tel-04361987

Submitted on 22 Dec 2023

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Mémoire

## Habilitation à Diriger des Recherches

### Contributions to the
Optimization of Wireless Broadcast/Broadband Systems :
Differentiated and Convergent Approaches

### Matthieu CRUSSIÈRE

Maître de Conférences à l'INSA de Rennes
Laboratoire IETR / Équipe de recherche SYSCOM

Soutenue le 24/11/2017 devant le jury composé de

### Rapporteurs

Geneviève Baudoin

Professeure à l'ESIEE, Paris

Andrea Tonello

Professeur à l'Université de Klagenfurt, Autriche

Jean-Marie Gorce

Professeur à l'INSA Lyon

### Examinateurs

Marie-Laure Boucheret

Professeure à l'ENSEEIHT, Toulouse

Catherine Douillard

Professeure à l'IMT-A, Brest

Jean-François Hélard

Professeur à l'INSA Rennes

Michel Terré

Professeur au CNAM, Paris

Bernard Uguen

Professeur à l'Université de Rennes 1

Luc Vanderdorpe

Professeur à l'Université de catholique de Louvain, Belgique
A mes très chers enfants,
Suzanna, Gaston, Marceau et Angéline,
sans qui tout cela n'aurait pas de sens.

Note : la mise en page de ce document a été réalisée à partir du style de mise en forme personnalisé disponible sous http://coursonline.insa-rennes.fr/course/view.php?id=90, en tant qu'évolution de la proposition opensource disponible sur http://ctan.org/pkg/pas-cv.
Introduction

Ce mémoire d'HdR se décompose en deux grandes parties. La première présente de façon détaillée tous les éléments factuels d'appréciation de mon parcours professionnel tant sur le plan de l'enseignement que de la recherche. Cette première partie est rédigée en français. La seconde partie propose une synthèse de mes activités de recherche, en faisant ressortir une structuration en trois axes et en mettant l'accent sur les principales contributions de ma recherche. Cette partie est rédigée en anglais. Enfin, de façon complémentaire à cette partie de synthèse une sélection de trois articles de revues est fournie en annexe du document concernant des points de ma recherche non développés dans le corps du document.

This HdR manuscript consists of two main parts. The first part contains all the details of my carrier path, exhaustively providing the elements to assess my teaching and research activities. This part is written in french. The second part of the document focuses on the main results of my research and provides a synthesis of the work according to three main axes. This part is written in english. Complementary to such an overview, a selection of three journal papers is given in appendix to highlight other contributions not detailed in the document.
<table><tbody><tr><td></td><td>Introduction</td><td>iii</td></tr><tr><td>Part. I</td><td>Parcours Professionnel</td><td>1</td></tr><tr><td></td><td>Préambule</td><td>3</td></tr><tr><td>Chap.</td><td>1 Curriculum Vitae succinct</td><td>5</td></tr><tr><td></td><td>1 État Civil</td><td>5</td></tr><tr><td></td><td>2 Situation professionnelle actuelle</td><td>5</td></tr><tr><td></td><td>3 Titres et qualifications</td><td>5</td></tr><tr><td></td><td>4 Parcours</td><td>6</td></tr><tr><td>Chap.</td><td>2 Activités liées à l'enseignement</td><td>7</td></tr><tr><td></td><td>1 Structuration des enseignements</td><td>7</td></tr><tr><td></td><td>2 Thématiques des enseignements</td><td>9</td></tr><tr><td></td><td>3 Investissements pédagogiques</td><td>10</td></tr><tr><td></td><td>4 Responsabilités administratives</td><td>12</td></tr><tr><td>Chap.</td><td>3 Activités liées à la recherche</td><td>14</td></tr><tr><td></td><td>1 Axes de recherche</td><td>14</td></tr><tr><td></td><td>2 Encadrement de la recherche</td><td>15</td></tr><tr><td></td><td>3 Contrats et projets collaboratifs</td><td>19</td></tr><tr><td></td><td>4 Production et valorisation scientifique</td><td>21</td></tr><tr><td></td><td>5 Responsabilités scientifiques, Rayonnement</td><td>24</td></tr><tr><td>Chap.</td><td>4 Publications</td><td>26</td></tr><tr><td>Part. II</td><td>Synthesis of the Research Works</td><td>35</td></tr><tr><td></td><td>Preliminaries</td><td>37</td></tr><tr><td>Chap.</td><td>5 Overview of the Research Activities</td><td>39</td></tr><tr><td></td><td>1 Classification</td><td>39</td></tr><tr><td></td><td>2 Overview of the studies</td><td>40</td></tr><tr><td></td><td>2.1 Wireless broadcast transmissions</td><td>40</td></tr><tr><td></td><td>2.2 Wireless broadband access</td><td>41</td></tr><tr><td></td><td>2.3 Broadcast/broadband convergent networks</td><td>42</td></tr><tr><td>Chap.</td><td>6 Optimization of Wireless Broadcast Transmissions</td><td>43</td></tr><tr><td></td><td>1 MIMO Schemes for Broadcast Systems</td><td>43</td></tr><tr><td></td><td>1.1 Motivations</td><td>43</td></tr><tr><td></td><td>1.2 Capacity of OFDM-MIMO Systems in SFN</td><td>44</td></tr><tr><td></td><td>1.3 Robust Distributed STBC for SFN</td><td>46</td></tr><tr><td></td><td>1.4 Fast Decodable Distributed STBC</td><td>49</td></tr><tr><td></td><td>1.5 conclusion</td><td>52</td></tr><tr><td></td><td>2 Practical design of PAPR reduction algorithms</td><td>52</td></tr><tr><td></td><td>2.1 Motivations</td><td>52</td></tr></tbody></table>
# Sommaire

<table><tbody><tr><td>2.2</td><td>PAPR Reduction and Tone Reservation Algorithms</td><td>53</td></tr><tr><td>2.3</td><td>Existing practical solutions</td><td>55</td></tr><tr><td>2.4</td><td>Proposed Algorithm based on New Kernel Definition</td><td>55</td></tr><tr><td>2.5</td><td>Performance results and analysis</td><td>59</td></tr><tr><td>2.6</td><td>Conclusion</td><td>63</td></tr><tr><td>3</td><td>Theoretical Analysis of Joint PAPR Reduction and Predistortion</td><td>64</td></tr><tr><td>3.1</td><td>Motivation</td><td>64</td></tr><tr><td>3.2</td><td>Transmitter Architecture Model</td><td>64</td></tr><tr><td>3.3</td><td>Analytical Derivations of the EVM</td><td>67</td></tr><tr><td>3.4</td><td>Application to Optimal Setting of the Transmitter</td><td>72</td></tr><tr><td>3.5</td><td>Conclusion</td><td>73</td></tr><tr><td>7</td><td>Optimization of the Wireless Broadband Access</td><td>75</td></tr><tr><td>1</td><td>Analysis of Time-Reversal Based Communications</td><td>75</td></tr><tr><td>1.1</td><td>Motivations</td><td>75</td></tr><tr><td>1.2</td><td>Time Reversal Filter Concept</td><td>76</td></tr><tr><td>1.3</td><td>TR-OFDM System Design</td><td>80</td></tr><tr><td>1.4</td><td>Achievable Rate in Single User Scenarios</td><td>83</td></tr><tr><td>1.5</td><td>Bit Error Rate Performance Analysis</td><td>86</td></tr><tr><td>1.6</td><td>Conclusion</td><td>88</td></tr><tr><td>2</td><td>Spatial Filtering for MU-MIMO in Moderate-Scale Antenna regime</td><td>89</td></tr><tr><td>2.1</td><td>Motivations</td><td>89</td></tr><tr><td>2.2</td><td>MU-MIMO Achievable Rate in the Moderate-scale antenna Regime</td><td>90</td></tr><tr><td>2.3</td><td>BER Performance with Partial Bandwidth Overlap</td><td>93</td></tr><tr><td>2.4</td><td>Extension to SS-OFDM waveform</td><td>99</td></tr><tr><td>2.5</td><td>Conclusion</td><td>102</td></tr><tr><td>3</td><td>Practical Beamforming Strategy for mmWave Communications</td><td>103</td></tr><tr><td>3.1</td><td>Motivations</td><td>103</td></tr><tr><td>3.2</td><td>System Model with Geometric-Based Channel Description</td><td>103</td></tr><tr><td>3.3</td><td>Digital Beamsteering Strategies</td><td>106</td></tr><tr><td>3.4</td><td>Leakage based power allocation</td><td>108</td></tr><tr><td>3.5</td><td>Leakage based power allocation</td><td>110</td></tr><tr><td>3.6</td><td>Conclusion</td><td>111</td></tr><tr><td>8</td><td>Broadcast / Broadband Convergence Studies</td><td>113</td></tr><tr><td>1</td><td>Semi-analytic analysis of dual mode Broadcast/Unicast Networks</td><td>113</td></tr><tr><td>1.1</td><td>Motivation</td><td>113</td></tr><tr><td>1.2</td><td>System Level Hybrid Broadband/Broadcast Wireless Network Model</td><td>114</td></tr><tr><td>1.3</td><td>Semi-Analytic Hybrid Network Performance Evaluation</td><td>118</td></tr><tr><td>1.4</td><td>Hybrid access performance analysis</td><td>119</td></tr><tr><td>1.5</td><td>Conclusion</td><td>121</td></tr><tr><td>2</td><td>Wireless hybrid broadcast/broadband network optimization</td><td>122</td></tr><tr><td>2.1</td><td>Motivation</td><td>122</td></tr><tr><td>2.2</td><td>Hybrid Network with adaptive broadcast coverage</td><td>123</td></tr><tr><td>2.3</td><td>Service Capacity Maximization</td><td>125</td></tr><tr><td>2.4</td><td>Energy Consumption Minimization</td><td>130</td></tr><tr><td>2.5</td><td>Conclusion</td><td>133</td></tr><tr><td>9</td><td>Research Perspectives</td><td>135</td></tr><tr><td>1</td><td>General context</td><td>135</td></tr><tr><td>2</td><td>Proposed Research tracks</td><td>135</td></tr><tr><td>2.1</td><td>Unified Model of High Power Transmitters Efficiency</td><td>135</td></tr><tr><td>2.2</td><td>Spatial Filtering for mmWave Systems</td><td>135</td></tr></tbody></table>
Sommaire

2.3 Optimized multi-mode communication networks 135

Bibliography 137

Part. III Annexes 147

Ann. 1 Article de revue R.7. 149

Ann. 2 Article de revue R.8. 173

Ann. 3 Article de revue R.14. 189

Ann. 4 Article de revue R.17. 191

Ann. 5 Article de conférence C.67 203
Partie I

<figure><img src="image_2.png" /></figure>

Parcours Professionnel
<figure><img src="image_3.png" /></figure>
# Préambule

Cette première partie de manuscrit a pour objectif d'apporter une vue générale de mon parcours tant sur le plan de la recherche que de l'enseignement. Elle aborde donc de façon synthétique mais néanmoins exhaustive l'ensemble des éléments représentatifs de mon activité, depuis ma thèse certes, mais surtout depuis ma nomination en tant que Maître de Conférences en février 2017. C'est dans cette partie que sont notamment consignés les différents éléments quantitatifs de mon dossier recherche : publications, encadrement doctoral, collaborations, activités contractuelles, etc. Mais, c'est également au sein de cette partie que je décris mon implication dans le processus de formation de mon établissement d'affectation, tant sur le plan strict de l'enseignement que des responsabilités administratives.

## Plan de la partie

<table><tr><td><b>Chapitre 1 : Curriculum Vitae succinct</b></td><td>p.5</td></tr><tr><td><b>Chapitre 2 : Activités liées à l'enseignement</b></td><td>p.7</td></tr><tr><td><b>Chapitre 3 : Activités liées à la recherche</b></td><td>p.14</td></tr><tr><td><b>Chapitre 4 : Publications</b></td><td>p.26</td></tr></table>
<figure><img src="image_4.png" /></figure>
## 1 ÉTAT CIVIL

<table><tr><td>Nom</td><td>Crussière</td></tr><tr><td>Prénom</td><td>Matthieu</td></tr><tr><td>Date et lieu de naissance</td><td>22 octobre 1979<br>Marennes (Charente-Maritime)</td></tr><tr><td>Situation familiale</td><td>Marié<br>4 enfants</td></tr><tr><td>Adresse Professionnelle</td><td>INSA de Rennes<br>Département SRC, bât. 6<br>20, Avenue des Buttes de Coësmes<br>CS 70839<br>35708 Rennes Cedex 7</td></tr><tr><td>Tél.</td><td>+33 (0)2 2323 8581</td></tr><tr><td>Mél.</td><td>matthieu.crussiere@insa-rennes.fr</td></tr><tr><td>Web</td><td>www.ietr.fr/perso/mcrussie</td></tr></table>

## 2 SITUATION PROFESSIONNELLE ACTUELLE

* **Maître de Conférence de classe normale, 63ᵉ section CNU**

**Etablissement** INSA Rennes
**d'affectation** Département "Systèmes et Réseaux de Communication" (SRC)

**Laboratoire de Recherche** Institut d'Électronique et de Télécommunications de Rennes (IETR)
UMR CNRS 6164
Département "Communications"
Équipe "Systèmes de Communications" (SYSCOM)

## 3 TITRES ET QUALIFICATIONS

**Depuis 2008** **Détenteur** de la PEDR/PES sans interruption, 63ᵉ section CNU
Première attribution : PEDR au 01/10/2008
Deuxième attribution : PES au 01/10/2012
Troisième attribution : PEDR au 01/10/2016
Dernier classement global au rang A
Classement par critère (Publ./Encadr./Rayon./Resp.) : A/A/A/B
**2006 Qualification** aux fonctions de Maître de Conférences
* Section 63 : "Électronique, Optronique et Systèmes"
* Section 61 : "Génie Informatique, Automatique et Traitement du Signal"

**2002-2005 Doctorat** de l'INSA de Rennes, mention Electronique
* Mention Très honorable
* Date de soutenance : 25 novembre 2005
* Titre de la Thèse : "Étude et optimisation de communications à haut-débit sur lignes d'énergie : exploitation de la combinaison OFDM/CDMA"
* Jury : Claude Berrou (P), Marie-Laure Boucheret (R), Pierre Duhamel (R), Jean-Marc Brossier (E), Jean-Yves Baudais (E), Jean-François Hélard (E)

**2002 Diplôme d'Etudes Approfondies** (DEA) de l'INSA de Rennes
* Spécialité : Électronique, Réseaux et Communications

**1997-2002 Titre d'Ingénieur** de l'INSA de Rennes
* Option : Électronique et Systèmes de Communications

**1996-1997 Baccalauréat**, Académie de Poitiers
* Série : Scientifique
* Mention : Bien

## 4 PARCOURS

**Depuis septembre 2013 Chercheur associé** à l'Institut de Recherche en Technologies B-COM à Rennes
* Laboratoire Intrastructures Réseaux (I&R)
* Mise à disposition à 20%

**Depuis février 2007 Maître de Conférences** à l'INSA de Rennes
* Département Systèmes et Réseaux de Communications (SRC)
* Classe Normale

**2005-2007 Attaché Temporaire d'Enseignement et de Recherche** (ATER) à l'Institut National des Sciences Appliquées de Rennes
* Département Électronique et Systèmes de Communications (ESC)
* Durée : 18 mois

**2002-2005 Doctorant** à l'Institut d'Électronique et de Télécommunications de Rennes, groupe Communications-Propagation-Radar (CPR)
* Direction de thèse : Prof. J.-F. Hélard
* Co-encadrement : CR CNRS J.-Y. Baudais
* Contributions au projet RNRT IDILE portant sur l'optimisation de systèmes multipor- teuses à étalement de spectre dans le contexte de communications à haut-débit sur courant porteur en ligne.
Comme indiqué dans mon CV au chapitre 1, mon établissement d'appartenance est l'INSA de Rennes, et je suis affecté au département d'enseignement SRC (Systèmes et Réseaux de Communication). Comme cela va être détaillé dans cette partie, j'effectue la quasi intégralité de mes enseignements au sein de ce département qui accueille des étudiants de niveau L3 à M2. Depuis la rentrée 2016, j'interviens également auprès des étudiants de la formation par apprentissage CDTI (Conception et Développement de Technologies Innovantes) de l'INSA de Rennes. Cette partie du document sera également l'occasion de détailler les différentes missions et responsabilités administratives que j'ai pu exercer en lien avec l'enseignement.

## 1 STRUCTURATION DES ENSEIGNEMENTS

Une vue d'ensemble de mes activités d'enseignement depuis mon poste d'ATER jusqu'à aujourd'hui est présentée sur les histogrammes de la figure 2.1. Ces histogrammes permettent de mettre rapidement en évidence deux aspects de mon déroulé de carrière en tant qu'enseignant :

- L'aspect volumétrique

- L'aspect typologique

Ces deux points sont commentés plus en détails ci-après. Par ailleurs, sur les histogrammes sont marquées par des noeuds numérotés (mathbf{Ni}) les principales étapes de refontes/modifications de programmes d'enseignement que j'ai effectuées ou auxquelles j'ai participé. Ces aspects seront détaillés dans le paragraphe 3.

### ► Volumétrie

Mon service d'enseignement annuel est bien entendu calibré sur la charge statutaire de 192 Heq TD, volume nominal auquel s'ajoutent tous les ans quelques dizaines d'heures supplémentaires. Comme le montrent les histogrammes, deux facteurs sont venus conditionner le volume total d'heures dispensées :

- Mon nombre d'heures complémentaires est borné à 50 Heq TD depuis l'obtention de la PEDR en octobre 2008, un an après ma nomination. J'ai ainsi effectué un service stable de 2008 à 2013 de 242 Heq TD par an.

- Depuis ma mise à disposition en septembre 2013 en tant que chercheur associé à l'institut de recherche et de technologie (IRT) B-com à Rennes, à hauteur de 20% de mon temps de travail, je bénéficie d'une décharge de service en équivalence horaire de 38 Heq TD à l'année. Depuis 4 ans, ma charge annuelle d'enseignement est donc réduite à 204 Heq TD (service réduit + heures complémentaires).

### ► Typologie

Mon investissement en cours, TD, TP et projets affiche une stabilité relative au cours des années. Il en est de même si l'on s'intéresse aux niveaux d'études auxquels correspondent mes enseignements : License (L2, L3), Maîtrise (M1, M2) ou Apprentissage (AP). Les fluctuations au cours du temps sont essentiellement dues aux évolutions des programmes d'enseignement et aux ventilations d'heures entre collègues en fonction des besoins/opportunités. Pour résumer les types d'enseignements dans lesquels je suis investi, deux points peuvent être notés :

- J'ai eu la chance de prendre la charge de deux cours magistraux dès ma prise de fonction, représentant un total d'environ 50 Heq TD. Aux modifications structurelles des maquettes d'enseignement prêt, ces cours constituent le socle stable de mon service depuis 10 ans. Pour le reste de ma charge, j'interviens selon les années, au sein de divers enseignements, en travaux pratiques et projets essentiellement, et en séances
<figure><img src="image_5.png" /><figcaption>**FIGURE 2.1**– Volume et type d'enseignements dispensés par année, de 2005 à 2017. En haut, volumes répartis par type : CM=cours magistral, TD=travaux dirigés, TP=travaux pratiques, PR=projets. En bas, volumes répartis par niveau : L2/L3=2e et 3e année de license, M1/M2=1e et 2e année de master, AP=apprentissage.</figcaption></figure>
## 2. Thématiques des enseignements

<figure><img src="image_6.png" /><figcaption>**FIGURE 2.2** Répartition moyenne des enseignements sur toute la carrière en % du volume total. A gauche : répartition en CM/TD/TP/PR. A droite : répartition par niveau L2/L3, M1/M2 et AP</figcaption></figure>

de travaux dirigés plus rarement. Cette tendance moyenne est reflétée par le diagramme de gauche de la figure 2.2.

- Jusqu'en 2015, mes enseignements étaient focalisés à environ 80% sur les niveaux L3 et M1. Depuis 2016, deux changements importants dans les enseignements à l'INSA ont fait évoluer cet équilibre. D'une part, des modifications importantes de maquettes pédagogiques ont conduit à redéployer un certain nombre des cours auxquels je participe du M1 vers la L3. D'autre part, l'ouverture de la formation par apprentissage (CDTI) m'a conduit à dispenser une part de mes cours vers cette formation. En moyenne depuis le début de ma carrière, la répartition par niveau de mes enseignements est présentée à droite sur la figure 2.2

## 2 THÉMATIQUES DES ENSEIGNEMENTS

D'un point de vue thématique, j'interviens sur des enseignements de deux natures :

- Thématique Signal & Communications,

- Thématique Électronique analogique

J'apprécie particulièrement cette double facette de mes enseignements qui me permet bien souvent de décloisonner les approches, d'effectuer des parallèles ou des connexions entre concepts ou bien encore de proposer des exemples à caractère transverse.

Dans la suite, la liste des différents modules dont j'assure la responsabilité ou la co-responsabilité, puis ceux auxquels je participe, est donnée. Une responsabilité de module signifie la définition du programme, la gestion des supports de cours, la proposition de sujets d'exercices et de manipulations pour les TP, ainsi que la gestion de l'évaluation des étudiants. Ces responsabilités peuvent être partagées.

### ► Responsabilités de modules :

**Depuis 2015 Traitement du signal déterministe, 2e partie, niveau L3**

*Volume :* 8H de cours, entre 8H et 12H de TD
*Contenu :* Conversion analogique-numérique / outils d'analyse temps-fréquence des signaux discrets / Changements de cadence

**Bases du traitement du signal déterministe, 2e partie, apprentissage**

*Volume :* 12H mélangeant cours/TD et TP
*Contenu :* Outils d'analyse temps-fréquence des signaux discrets
## Systèmes linéaires numériques, niveau L3

Volume : 20H mélangeant cours et TD

Contenu : Outils d'analyse des systèmes linéaires discrets / Filtrage numérique

## Systèmes de communication, 1ère partie, niveau L3

Volume : 12 H de cours, 4H de TP

Contenu : Modèle de chaînes de communications / Transmissions sur fréquence porteuse / Modèle des signaux à bande étroite

## 2007-2015 Traitement numérique du signal, niveau M1

Volume : 24 H de cours

Contenu : Outils d'analyse des systèmes et signaux à temps discrets

## Traitement du signal pour les communications analogiques, niveau L3

Volume : 14 H de cours

Contenu : Outils d'analyse des performances des modulations analogiques

### ▶ Autres implications :

#### Depuis 2011 Communications Numériques, niveau M1

Volume : variable entre 8 et 16 H de TD, entre 6H et 20H de TP

Contenu : Constellations, critères de Nyquist, calculs de performances, OFDM

#### Récepteurs avancés, niveau M2

Volume : variable entre 2H et 4H de TD, 6H de TP

Contenu : Techniques d'égalisation, filtrage adaptatif

#### Radiocommunications, niveau M1

Volume : 12H de TP

Contenu : Caractérisation des canaux de propagation, sondage de canal

#### Depuis 2007 Electronique analogique, niveau L3

Responsable des TP

Volume : variable entre 14 et 28 H de TP, 12H de projet

Contenu : lois de l'électronique linéaires, diodes et transistors

## Systèmes linéaires analogiques, niveau L3

Responsable des TP

Volume : variable entre 10 et 20 H de TP, 24H de projet

Contenu : Amplificateur opérationnel, systèmes bouclés, filtrage, oscillations

## Projets et bureaux d'étude, niveau M1/M2

Volume : variable selon les années, 15 H au maximum

Contenu : suivi de groupes d'étudiants sur des projets transversaux sur l'année ou le semestre, du cahier des charges à la réalisation finale.

## 3 INVESTISSEMENTS PÉDAGOGIQUES

Dans cette partie, je souhaite mettre en avant mon intérêt appuyé pour la pédagogie en montrant mon investissement pour la mise en place de nouveaux enseignements ou pour leur évolution. Il est bien évident que cet investissement va de soi pour un enseignant, mais la double vie de l'enseignant-chercheur peut parfois conduire à sur-favoriser une activité ou détriment de l'autre. Je m'efforce donc de consacrer un temps suffisant à la réflexion (individuelle ou collective) dans le but de faire évoluer mon enseignement à la fois sur le fond (mise à jour du programme) et la forme (supports pédagogiques, façon d'enseigner). Sur ce dernier point, j'envisage d'ailleurs dès cette année d'expérimenter dans un de mes cours l'utilisation de la pédagogie dite par "classe inversée", dans laquelle certaines séances de cours (typiquement 2 sur 3) seront essentiellement le lieu de discussions et d'échanges autour des questions des étudiants et de problèmes posés, la théorie étant pour l'essentielle disponible en ligne ou sur documents ciblés que je mettrai à la disposition des étudiants pour qu'ils puissent travailler par avance.
# 3. Investissements pédagogiques

## ▶ Création/évolution des enseignements :

Sur les histogrammes présentés précédemment à la figure 2.1 sont indiquées les principales actions (numérotées de A1 à A12) que j'ai menées au fil des ans pour faire évoluer les différents enseignements dont j'ai eu la charge ou auxquels j'ai participé. Il a pu s'agir de la construction de nouveaux cours ou projets, ou bien du reformatage de certains.

**A1 Construction d'un module dit de "sensibilisation"**

Niveau L2, en collaboration avec 2 collègues

Actions menées : participation à la mise en oeuvre d'un mini-projet pour faire découvrir l'électronique fondamentale aux étudiants de 1er cycle universitaire. Application : mise en forme de signaux de télévision à partir de montages à composants discrets.

Dimensionnement de l'ensemble des circuits et écriture d'un polycopié associé.

**A2, A3 Reformatage d'un module de "traitement numérique du signal"**

Niveau M1,

Actions menées : redéfinition d'un module complet sur les outils d'analyse et de traitement des signaux et systèmes à temps discret. Proposition de 6 séances de travaux pratiques associés au cours, avec manipulations sous Matlab.

**A4, A5 Reformatage d'un module de "Modulations analogiques"**

Niveau L3,

Actions menées : redéfinition d'un module complet sur les notions de transmissions de l'information sur onde porteuse. Proposition de 5 séances de travaux pratiques associés au cours, avec manipulations sous Matlab et sur analyseur de spectre.

**A6, A7 Proposition de projets tutorés d' "électronique analogique"**

Niveau L3, en collaboration avec 2 collègues

Actions menées : participation à la définition de deux projets de fin de semestre en électronique analogique regroupant l'ensemble des notions vues au cours. Définition des sujets, dimensionnement et mise en oeuvre et tests des circuits. Applications : observation automatique de caractéristiques de transistors à l'oscilloscope, réalisation d'un mini-analyseur de spectre.

**A8 Proposition de nouveaux exercices en "communications numériques"**

Niveau M1, en collaboration avec 1 collègue

Actions menées : participation à la définition de nouveaux sujets d'exercices suite à l'évolution du cours de communications numériques. Recherche de mises en situation pratique pour le dimensionnement système (problématiques de type ingénieur).

**A9 Reformatage des TPs en "communications numériques"**

Niveau M1, en collaboration avec 3 collègues

Actions menées : participation à la migration de l'ensemble des manipulations de TPs vers des plateformes radiologicielles (USRP). Redéfinition complète du programme de TP, préparation des programmes, tests, rédaction des sujets.

**A10, A11 Reformatage de deux modules de "traitement du signal"**

Niveau L3, en collaboration avec 4 collègues

Actions menées : participation à la redéfinition complète du programme de traitement du signal sur 18 mois et reformatage des séances de cours/TD/TP associés. Mise à jour des supports, des exercices et des manipulations de TP.

**A12 Nouveau cours de "traitement du signal" en formation par apprentissage**

Niveau L3, en collaboration avec 2 collègues

Actions menées : participation à l'adaptation/redéfinition du programme de traitement du signal sur 12 mois pour des étudiants en apprentissage. Modification de la pédagogie : approche conjointe théorie, exercices et pratique sous Matlab.
## ► Supports pédagogiques :

Aux actions détaillées précédemment viennent s'ajouter au fil de l'eau la mise à jour régulière des supports pédagogiques. Ceux-ci diffèrent naturellement en fonction de la nature de l'enseignement, à savoir en cours ou en TP, et correspondent à un choix sur la pédagogie suivie :

- Pour les cours magistraux, je privilégie les cours au tableau pour leur côté plus interactif et spontané. Cela est possible dans la mesure où je fournis aux étudiants des polycopiés de cours volontairement très complets (cf. liste ci-dessous). La prise de notes reste donc à volume raisonnable et n'empêche pas la concentration sur le fond. Je peux donc ainsi consacrer l'essentiel du temps en cours pour expliciter et illustrer les principales notions du programme, pointer les aspects les plus techniques, mener les démonstrations les plus importantes et proposer les premiers exemples d'application. Il s'agit également d'attirer l'attention sur les pièges ou erreurs fréquemment rencontrés. Le cours magistral consiste donc en la prédigestion d'un contenu déjà disponible (le polycopié), censée faciliter l'assimilation finale qui reste évidemment du ressort de l'étudiant lui-même. Comme mentionné plus haut, j'envisage de tester d'autres formes de pédagogie où l'étudiant se montre plus acteur que spectateur du cours.

- Pour les travaux pratiques, au-delà de la fourniture d'un recueil de sujets à traiter en séance, je dispose pour chaque session de laboratoire d'un jeu de transparents (cf. liste ci-dessous) permettant de lancer les manipulations et de faire des points réguliers au tableau. Cela permet de pointer les principales observations et conclusions importantes de chaque manipulation, mais également de cadencer les séances en resynchronisant les différents binômes d'étudiants. Pour les simulations logicielles (ex : Matlab), je fournis sur Moodle l'ensemble des codes corrigés pour que les étudiants puissent travailler en dehors des séances encadrées.

**Polycopiés**

de cours

Niveau L3, chapitres 5 à 7, 40 pages

**Module de "systèmes linéaires numériques"**

Niveau L3, polycopié complet, 80 pages

**Module de "systèmes de communications"**

Niveau L3, chapitres 1 à 4, 80 pages

**Module de "Traitement numérique du signal"**

Niveau L3, polycopié complet, 150 pages

**Supports**

de TP

Niveau L3, sujets de TP (8 manipulations), transparents associés

**Module de "systèmes linéaires numériques"**

Niveau L3, sujets de TP (4 manipulations), codes Matlab associés

**Module de "systèmes linéaires analogiques"**

Niveau L3, sujets de TP (5 manipulations), transparents associés

**Module de "Communications numériques"**

Niveau M1, sujets de TP (6 manipulations), transparenst associés

## 4 RESPONSABILITÉS ADMINISTRATIVES

Depuis ma nomination à l'INSA de Rennes en février 2007, je me suis impliqué comme chacun de mes collègues dans la prise en charge de responsabilités d'ordre administrative liées au fonctionnement du département d'enseignement. L'historique de ces responsabilités est donné ci-dessous.

**Depuis février 2017**

**Chargé de mission pour le département SRC**

Missions : assistance au directeur de département pour la gestion globale de la formation pédagogique (suivi des maquettes d'enseignement, tenue des indicateurs de la formation, suivi du budget d'investissement), participation partielle aux réunions de co-direction au niveau de l'établissement INSA.
4. Responsabilités administratives

Depuis 2013 Membre élu au conseil de département
Département SRC

De 2009 à 2016
Responsable de la 3e année du département SRC
Missions : gestion des études et des étudiants en L3 au département SRC.
Suivi et mise à jour de la maquette pédagogique, construction des emplois du temps, suivi au quotidien des étudiants, préparation du jury d'année, liens avec le secrétariat.

De 2007 à 2011
Responsable du module de sensibilisation SRC
Missions : gestion du programme destiné aux étudiants de 1er cycle INSA, organisation des ateliers de découverte, des visites en entreprise et des tables rondes.
Cette partie est consacrée à la présentation synthétique de mes activités de recherche avec le but de faire ressortir les critères objectifs d'évaluation que sont l'encadrement de la recherche, la production scientifique, la participation à des projets collaboratifs ou la prise de responsabilités.

Mon laboratoire de rattachement est l'IETR (Institut d'Électronique et de Télécommunications de Rennes), et plus précisément l'équipe SYSCOM (Système de Communications) du département "Communications". Cette équipe, partagée géographiquement entre l'Université de Nantes et l'INSA Rennes est la plus importante du laboratoire en termes de nombre de personnes. Depuis janvier 2017, suite à la mise en place de la nouvelle organisation de l'IETR pour la période 2017-2020, je suis co-responsable de l'équipe pour la partie renaise de l'équipe. Cette équipe compte environ 9 chercheurs et enseignant-chercheurs (aux pourcentages d'affectation prêt), dont 5 HDR parmi lesquels 3 professeurs des universités. Il faut également noter que je suis impliqué au sein de l'IRT B-Com à Rennes par le biais d'une mise à disposition à 20% de mon temps de travail, soient 40 jours par an. Une part de mes activités de recherche s'inscrit donc dans le cadre du laboratoire IR (Interfaces Réseaux) de l'IRT.

## 1 AXES DE RECHERCHE

Depuis mes débuts dans le monde de la recherche académique, mes activités ont eu pour dénominateur commun la recherche d'efficacité dans les systèmes de communications numériques en s'appuyant essentiellement sur l'optimisation des couches physiques et d'accès des systèmes. Au fil des ans, différentes facettes de cette ligne se sont exprimées, au gré des opportunités et des envies, entre une approche système et des considérations plus algorithmiques et mathématiques. En faisant l'historique des principaux thèmes traités, il est possible de dégager deux phases dans mes activités :

- La première phase, qui s'écoule de 2002 à 2010 environ inclut mes travaux de thèse et ceux des premières années qui la suivirent. Durant cette période, mes activités se sont concentrées sur l'optimisation des schémas de modulation hybridant l'étalement de spectre et l'OFDM, encore appelées schémas de modulation à porteuses multiples à précodage linéaire. Mes travaux ont alors porté sur la recherche de solutions de synchronisation, d'estimation de canal et d'allocation des ressources dans différents contextes applicatifs, des liaisons filaires aux réseaux sans fil.

- La seconde phase, qui a démarré vers 2009 a progressivement conduit à la structuration actuelle de mes activités, dans le prolongement des travaux effectués dans la première phase. Mes travaux de recherche actuels s'articulent donc autour de 3 thèmes principaux :

1. Algorithmie et performances théoriques pour les systèmes de radiodiffusion,

2. Algorithmie et performances théoriques pour le partage de la ressource dans les réseaux d'accès radio,

3. Modélisation et analyse de performances des réseaux hybrides ou hétérogènes.

Une autre grille de lecture de mes activités de recherche peut-être celle des méthodes et outils utilisés et développés lors des différentes études. Les principales approches suivies, souvent de façon transverse aux thèmes listés ci-dessus, sont les suivantes :

- Estimation paramétrique,

- Optimisation sous contrainte,

- Modélisation stochastique de signaux et systèmes,

- Analyse analytique et semi-analytique de performances.
## 2. Encadrement de la recherche

Dans la suite de ce chapitre, l'ensemble des données et critères objectifs en lien avec mes activités de recherche seront exposées de façon synthétique, pour l'ensemble de mon parcours et pour les deux phases identifées à l'instant. Dans la deuxième partie du document (cf. partie 2) consacrée à la synthèse de mes activités de recherche, seules les contributions associées à la seconde phase de mon parcours seront détaillées, celles de la première phase étant simplement rapidement décrites en guise de préambule dans le chapitre 5.

## 2 ENCADREMENT DE LA RECHERCHE

Depuis ma prise de poste en tant qu'ATER il y a 12 ans, j'ai effectué le co-encadrement de 18 thèses, dont 15 soutenues, avec un taux d'encadrement variant de 33% à 65% selon les cas. La figure 3.1 donne une vue globale de mon activité d'encadrement doctoral au fil des années, avec en légende la thématique associée à chaque thèse conformément aux axes identifiés dans le paragraphe précédent. En complément, sur ce diagramme sont indiqués les taux d'encadrement par thèse, ainsi que les thèses qui ont fait l'objet d'une co-tutelle ou/et d'une implication dans un projet collaboratif. Enfin, la durée moyenne des thèses, évaluée à 3 ans et 4 mois, est mentionnée pour information sur cette figure. Cette figure met en évidence mon implication continue et soutenue de l'encadrement de thèses, avec en rythme souvent supérieur à 4 thèses en cours.

<figure><img src="image_7.png" /><figcaption>FIGURE 3.1– Déroulement chronologique des thèses co-encadrées et classification thématique.</figcaption></figure>

Outre l'encadrement de thèses, j'ai également réalisé celui de 9 stages de Master d'une durée de 4 à 5 mois chacun. Ces stages ont pour la plupart été menés en lien avec les travaux de thèse des doctorants, si bien que ces derniers en ont également été co-encadrants. Enfin, à ces activités d'encadrement s'ajoute également le suivi de 5 post-doctorants, même s'il est naturellement entendu dans ce cas que le travail de suivi s'apparente davantage à un travail collaboratif, étant donné l'autonomie et l'expérience de ce type de candidats.

Dans les sections qui suivent sont données les listes exhaustives et détaillées de l'ensemble des stagiaires et doctorants encadrés, ainsi que des post-doctorants avec qui j'ai travaillé.

► Liste des thèses co-encadrées :
**Émeric GUEGUEN**
"Etude et optimisation des techniques UWB haut débit multibandes OFDM"
Soutenue le 14 janvier 2009
Directeur de Thèse : J.F. Hélard (50%)
Co-encadrant : M. Crussière (50%)
Position actuelle du Docteur : chargé d'affaires à EDF-TDG, France

**Ayman KHALIL**
"Procédés inter-couches d'allocation de ressource pour les futurs systèmes UWB multiporteuse à haut-débit"
Soutenue le 13 septembre 2010
Directeur de Thèse : J.F. Hélard (50%)
Co-encadrant : M. Crussière (50%)
Position actuelle du Docteur : Enseignant-chercheur à l'UIL, Liban

**Pierre-Oudomsack PASQUERO**
"Optimisation de Systèmes de télévision numérique terrestre : estimation de canal, synchronisation et schémas multi-antennes distribués"
Soutenue le 27 juin 2011
Directeur de Thèse : J.F. Hélard (50%)
Co-encadrant : M. Crussière (50%)
Position actuelle du Docteur : Ingénieur de recherche à DGA-MI, France

**Ming LIU**
"Analyse et optimisation des systèmes asiatiques de diffusion de télévision numérique terrestre et mobile"
Soutenue le 30 mars 2011
Directeur de Thèse : J.F. Hélard (50%)
Co-encadrant : M. Crussière (50%)
Position actuelle du Docteur : Enseignant-chercheur à l'université de Pékin, Chine

**Karima RAGOUBI**
"Techniques de raccourcissement de canal pour systèmes OFDM"
Soutenue le 8 décembre 2011
Directeur de Thèse : M. Hélard (50%)
Co-encadrant : M. Crussière (50%)
Position actuelle du Docteur : Chef de projet déploiement réseaux à ERDF, France

**Samar SINDIAN**
"Optimisation de l'allocation de ressource pour les réseaux WPAN maillés à haut-débit"
Soutenue le 17 septembre 2014
Directeur de Thèse : J.F. Hélard (30%)
Co-encadrants : A. Khalil (25%), M. Crussière (45%)
Position actuelle du Docteur : chargée d'enseignement à l'IUL, Liban

**Nicolas CORNILLET**
"Convergence des réseaux de télécommunications mobiles et de télédiffusion : modélisation et évaluation des performances d'un réseau hybride LTE/DVB-T2"
Soutenue le 18 décembre 2013
Directeur de Thèse : M. Hélard (50%)
Co-encadrant : M. Crussière (50%)
Position actuelle du Docteur : Ingénieur chez Nokia, France

**Thierry DUBOIS**
"Application du retournement temporel aux systèmes multi-porteuses : propriétés et performances"
Soutenue le 12 février 2013
Directeur de Thèse : M. Hélard (50%)
Co-encadrants : M. Crussière (50%)
Position actuelle du Docteur : Chargé d'affaires chez ALTRAN, France
## 2. Encadrement de la recherche

**Hua FU** "Optimisation de la ressource spectrale dans les systèmes multi-antennes multi-
utilisateurs avec recouvrement partiel de bande"

Soutenue le 22 mai 2015

Directeur de Thèse : M. Hélard (35%)

Co-encadrant : M. Crussière (65%)

Position actuelle du Docteur : Post-Doc à l'université de Cherbrooke, Canada

**Ralph MOUNZER** "Nouveaux algorithmes de réservations de porteuses pour la réduction de PAPR des signaux multiporteuse"

Soutenue le 15 décembre 2015

Directeur de Thèse : J.F. Hélard (35%)

Co-encadrants : Y. Nasser (30%), M. Crussière (35%)

Position actuelle du Docteur : Ingénieur, USA

**Antoine ROZÉ** "Massive MIMO, une approche angulaire pour les futurs systèmes multi-
utilisateurs aux longueurs d'onde millimétriques"

Soutenue le 17 octobre 2016

Directeur de Thèse : M. Hélard (33%)

Co-encadrants : C. Langlais (33%), M. Crussière (33%)

Position actuelle du Docteur : Ingénieur, Australie

**Pape-Aboulaye FAM** "Définition d'un système de diffusion hertzien de contenus multimédias convergent avec les réseaux broadcast et mobiles"

Soutenue le 9 février 2017

Directeur de Thèse : M. Hélard (40%)

Co-encadrants : P. Brétillon (20%), M. Crussière (40%)

Position actuelle du Docteur : Ingénieur de recherche à TDF, France

**Ali CHEAITO** "Recherche de solutions conjointes et adaptatives de réduction de PAPR et de prédistrortion pour les systèmes de radio intelligente utilisant les formes d'onde à porteuses multiples"

Soutenue le 10 mars 2017

Directeur de Thèse : M. Hélard (33%)

Co-encadrants : Y. Louët (33%), M. Crussière (33%)

Position actuelle du Docteur : Post-Doc à Supélec, France

**Mohamad ZALGHOUT** "Algorithmes d'attachements dans les réseaux hétérogènes WLAN et cellulaires"

Soutenance prévue le lundi 23 octobre 2017

Directeur de Thèse : J.F. Hélard (30%)

Co-encadrants : A. Khalil (20%), Samih Adbul-Nabi (20%), M. Crussière (30%)

**Louis-Adrien DUFRENE** "Recherche de solutions d'adaptation des réseaux GSM aux nouvelles contraintes des communications vers les objets"

Àsoutenir en novembre 2017

Directeur de Thèse : J.F. Hélard (40%)

Co-encadrants : J. Schwoerer (20%), M. Crussière (40%)

**Ali MOKH** "Optimisation des schémas de modulation spatiale"

Démarrée le 1 octobre 2015

Directeur de Thèse : M. Hélard (50%)

Co-encadrant : M. Crussière (50%)

**Mohamed SHEHATA** "Précodage spatial hybride analogique-numérique pour les communications en
onde millimétrique"

Démarrée le 1 octobre 2016

Directeur de Thèse : M. Hélard (33%)

Co-encadrant : P. Pajusco (33%), M. Crussière (33%)
**Ahmad** "Modélisation et optimisation de réseaux hybrides broadband/broadcast"
**SHOKAIR** Démarrée le 1 octobre 2016
Directeur de Thèse : M. Hélard (33%)
Co-encadrants : Y. Nasser (33%), (M. Crussière (33%))

► Liste des Post-Doctorants suivis :

**Youssef** "Schémas MIMO pour les réseaux de diffusion"
**NASSER** octobre 2007 à septembre 2009
Projet : B21C

**Ming** "Schémas MIMO pour les réseaux de diffusion"
**LIU** janvier 2011 à janvier 2012
Projet : Engines

**Jean-Christophe** "Modèles de statistique d'erreurs des codes LDPC DVB-S2"
**SIBEL** octobre 2012 à octobre 2014
Projet : OptiSaT2

**Ferdaouss** "Modèles d'abstraction du protocole HbbTV2.0 sur couche PHY DVB-T2"
**MATTOUSSI** juin 2016 à décembre 2017
Projet : AdicTV

**Krishna** "Optimisation des techniques de réduction de PAPR pour les normes DVB-T2 et ATSC3.0"
**BULUSU** septembre 2016 à décembre 2017
Projet : GreenTEA

► Liste des stages de Master co-encadrés :

**Eddy** "Etude de processus de synchronisation par la technique du pilote étalé"
**CHOLLET** septembre-décembre 2008
Encadrement : O.P. Pasquero, M. Crussière, J.F. Hélard

**Elias** "Allocation dynamique de ressources sous contrainte de qualité de service dans les réseaux UWB"
**NAJJAR** mars-juillet 2009
Encadrement : A. Khalil, M. Crussière, J.F. Hélard

**Hassan** "Allocation de ressource et ordonnancement distribué dans les réseaux WPAN"
**ALI-AHMAD** mars-juillet 2010
Encadrement : A. Khalil, M. Crussière, J.F. Hélard

**Rana** "Allocation de ressource temps-fréquence dans les réseaux WPAN"
**DIAB** mars-juillet 2011
Encadrement : A. Khalil, M. Crussière, J.F. Hélard

**Imad** "Etude d'une architecture MESH pour les futurs réseaux WPAN"
**JAMIL** mars-juillet 2012
Encadrement : S. Sindian, A. Khalil, M. Crussière, J.F. Hélard

**Ali** "Analyse conjointe des fonctions de prédistortion et de réduction de facteur de crête sur les signaux OFDM"
**CHEAITO** mars-juillet 2013
Encadrement : M. Crussière, J.F. Hélard
3. Contrats et projets collaboratifs

**Daniel KOBEISSI** "Analyse des statistiques d'erreurs sur paquets MPEG-TS dans les réseaux DVB-T2"

mars-juillet 2016

Encadrement : F. Mattoussi, M. Crussière, J.F. Hélard

Syed- Muhammad "Etude analytique du spectre des signaux multiporteuses dans un contexte d'amplification de puissance non-linéaire"

FAHAD mars-juillet 2016

Encadrement : A. Cheaito, M. Crussière, J.F. Hélard

3 CONTRATS ET PROJETS COLLABORATIFS

L'équipe de recherche SYSCOM de l'IETR possède une activité contractuelle et partenariale soutenue. Aux côtés des collègues de l'équipe, une part importante de mon temps recherche est consacrée à la participation et au suivi des différents projets. Ainsi, j'ai donc eu une implication conséquente dans les projets, en prenant souvent des responsabilités de lots (Work-Packages), potentiellement importantes, comme au sein des projets européens B21C et ANR MCube. Au total depuis 10 ans, j'ai collaboré à 19 projets, qu'ils soient de dimension régionale, nationale, européenne ou encore industrielle comme détaillé ci-après. Ces projets sont bien entendu un moyen d'entretenir des relations privilégiées avec le monde industriel et académique. Mais au-delà, il s'agit aujourd'hui d'un vecteur important du financement de la recherche pour l'équipe (cf. implication des doctorants dans les projets figure 3.1).

La liste des différents projets et les détails les concernant est donnée ci-après. En complément, une vue synthétique est proposée sur la figure 3.2 : répartition chronologique des différents projets/contrats, classement par type et signalétique de la nature de mon implication au plan administratif (montage, responsabilité, gestion).

<figure><img src="image_8.png" /><figcaption>FIGURE 3.2– Chronologie et classification des différentes implications contractuelles et projets.</figcaption></figure>
Contrat d'étude "Etude et optimisation de la combinaison des techniques UWB-MS et CDMA haut-débit et extension aux WLANs"

Type de client : opérateur de télécommunications, 2005-2007 (36 mois)

Implication personnelle : suivi des études

OMEGA "Home Gigabit Area, Converged, Ultra High Speed Home and Access Networks"

Projet Européen IST FP7, 2008-2010 (36 mois)

20 partenaires : hollandais, allemands, français, italiens, grecs, slovènes, etc.

Implication personnelle : contributeur au montage du projet, suivi des études

B21C "Broadcast for the 21st Century")

Projet Européen CELTIC, 2007-2009 (36 mois)

32 partenaires : allemands, italiens, anglais, suédois, finlandais, français, etc..

Implication personnelle : responsable de lot, suivi des études

Mobile TV "Analyse des normes de télévision mobiles mondiales et optimisation des récepteurs associés"

Projet Région Bretagne du pôle "Image & Réseaux", 2007-2009 (36 mois)

Partenaires : Teamcast, Silembia, Bretagne International, BTIC.

Implication personnelle : suivi des études

ENGINES "Enabling Next Generation Networks for Broadcast Services"

Projet Européen CELTIC, 2010-2012 (36 mois)

32 partenaires : allemands, italiens, anglais, suédois, finlandais, français, etc..

Implication personnelle : contributeur au montage projet, suivi des études

Mcube "Mobile Multi Media"

Projet ANR, 2010-2013 (36 mois)

Partenaires : Orange Labs, CNES, ALU, MERCE, Telecom Bretagne, Teamcast, Parrot

Implication personnelle : contributeur au montage projet, responsable de lot, suivi des études

TRIMARAN "Time-Reversal for Green communicAtions based on MicRo-structured ANten-nas"

2011-2013, 40 mois

Projet ANR

Partenaires : Orange Labs, Inst. Langevin, Thalès, Telecom Bgne, TRcom.

Implication personnelle : contributeur au montage projet, suivi des études

OptiSaT2 "Optimisation des Transmission Satellite de 2nd génération"

Projet FUI, 2012-2014 (26 mois)

Partenaires : Enensys Tech, TDF, SmartDTV, Telecom Paris Tech

Implication personnelle : contributeur au montage projet, suivi des études

Contrat d'étude "Etude de faisabilité d'exploitation des réseaux GSM pour l'intégration d'objets communicants au sein des réseaux de communications"

Type de client : opérateur de télécommunications, 2014 (8 mois)

Implication personnelle : proposition de l'étude, responsable de contrat, suivi des études

PAPRICA "PAPR Iterative Compression Algorithms"

Projet Région Bretagne du pôle "Images et Réseaux", 2012-2015 (30 mois)

Partenaires : Teamcast, Digidia

Implication personnelle : contributeur au montage projet, responsable de lot, suivi des études
## 4. Production et valorisation scientifique

<table><caption>TABLE 3.1- Chiffres globaux de publications et citations 2003-2017 (source Google Scholar, septembre 2017)</caption><tr><td>Nombre de publications en revues internationales à comité de lecture (ACL)</td><td>24</td></tr><tr><td>Nombre de communications en conférences internationales (ACTI)</td><td>93</td></tr><tr><td>Nombre de communications en conférences nationales (ACTN)</td><td>6</td></tr><tr><td>Nombre de chapitres d'ouvrages scientifiques (OS)</td><td>4</td></tr><tr><td>Nombre de brevets</td><td>4</td></tr><tr><td>Nombre total de citations</td><td>689</td></tr><tr><td>H-Index</td><td>15</td></tr></table>

<table><tr><td>RS-COM</td><td>"Réseaux et Systèmes pour les Communications"<br>Projet ANR fléché IRT-BCOM, 2013-2016 (36 mois)<br>Partenaires : IRT-BCOM, UR1, Telecom Bgne, Orange Labs, TDF, Siradel<br>Implication personnelle : contributeur et suivi des études</td></tr><tr><td>AdicTV</td><td>"Optimisation des transmissions non-linéaires sur les réseaux de diffusion"<br>Projet FUI, 2015-2019 (29 mois)<br>Partenaires : Enensys, TDF, HTTV, Quadrille, TelecomParisTech<br>Implication personnelle : contributeur au montage projet, responsable du contrat pour l'INSA, responsable de lot, suivi des études</td></tr><tr><td>Spatial Modulation</td><td>"Spatial Modulation and reconfigurable antennas for high-rate connectivity to mobile and energy autonomous sensors"<br>Projet ANR, 2016-2019 (42 mois)<br>Partenaires : Orange Labs, IMT Atl., Inst. Langevin, Centrale Supélec, TR-COM<br>Implication personnelle : contributeur au montage du projet, suivi des études</td></tr><tr><td>GreenTEA</td><td>"Green Transmission Efficiency Algorithms"<br>Projet Européen EUROSTAR, 2016-2018 (24 mois)<br>Partenaires : Teamcast, TRYO Communications<br>Implication personnelle : responsable de lot, suivi des études</td></tr><tr><td>Convergence TV</td><td>"Algorithms for the convergence of worldwide Digital Television standards"<br>Projet FUI, 2017-2019 (24 mois)<br>Partenaires : Teamcast, TDF, BroadPeak, MotionSpell, ATEME, Canal+<br>Implication personnelle : suivi des études</td></tr></table>

# 4 PRODUCTION ET VALORISATION SCIENTIFIQUE

## ► Analyse bibliométrique de la production scientifique

La liste complète et détaillée de mes publications (revues, conférences, chapitres d'ouvrages et brevets) est donnée dans la partie 4 du document. Je fournis dans ce paragraphe une analyse synthétique de ma production scientifique sous la forme de diagrammes et tableaux.

Tout d'abord, le tableau 3.1 donne les chiffres globaux pour l'ensemble de mes publications et citations, ainsi qu'une évaluation du fameux H-index. L'ensemble de ces données sont issues de ma page Google Scholar accessible librement en consultation en ligne.

Ensuite, sur les figures 3.3 et 3.4 l'ensemble des données bibliométriques sont compilées et respectivement traduites sous la forme d'un histogramme temporel et d'un diagramme sectoriel, chacun tenant compte de la classification des publications par type.

## ► Actions de valorisation de la recherche
<figure><img src="image_9.png" /></figure>

FIGURE 3.3– Évolution chronologique du nombre de publications et classification par type.

<figure><img src="image_10.png" /></figure>

FIGURE 3.4– Répartition moyenne des publications par types sur la période 2003 à 2017.
## 4. Production et valorisation scientifique

Outre l'activité "classique" de publication en revues et conférences, j'ai mené, souvent en commun avec d'autres collègues, d'autres formes de dissémination et de valorisation des travaux listées ci-dessous. Ce type d'actions se sont intensifiées ces dernières années.

**Tutoriaux en conférences**

"The Time Reversal Paradigm : close relations with spatial filtering/beamforming and large-scale antenna systems"

IEEE Asia Pacific Wireless and Mobile Conference (APWiMob'15), Bandung, Indonesia, août 2015.

M. Hélard, M. Crussière et Y. Kokar

"Application of Time Reversal Principles to Wireless Communications : from SingleUser SISO to MultipleUser Large Scale MIMO Scenarios"

International Conference on Software, Telecommunications and Computer Networks 2015 (SoftCom'15), Split, Croatia, sept. 2015.

M. Hélard, M. Crussière et J.C. Prévotet

**Papiers invités**

"Quantifying the Memory Effects of Power Amplifiers : EVM Closed-Form Derivations of Multicarrier Signals"

IEEE International Globecom Conference 2017, Special WCL session, Singapore, dec. 2017

A. Cheaito, M. Crussière, J.F. Hélard et Y. Louët

"Time Reversal Based Beamforming for Wireless Communications : A Theoretical Analysis from Moderate-Scale to Large-Scale Antenna Systems"

5th IEEE International Conference on Communications and Networking (COMNET'15), Hammamet, Tunisia, nov. 2015

M. Crussière, H. Fu et M. Hélard

**Journées GDR**

"Retournement temporel pour des systèmes multi-antennes et multi-porteuses" journée scientifique conjointe des GDR ISIS et GDR ONDE "Développements récents en focalisation et communication par retournement temporel", 26 sept. 2013

M. Hélard, T. Dubois et M. Crussière

"Optimisation de la ressource spectrale pour les systèmes MU-MIMO avec recouvrement fréquentiel partiel"

journée scientifique conjointe du GDR ISIS "L'éco-radio", 6 mai 2015

H. Fu, M. Crussière et M. Hélard

**Séminaires industriels**

"Preuve de concept d'une transmission MISO à 2.4GHz utilisant le concept de retournement temporel"

Salon de la recherche d'Orange Labs, Orange Gardens, Issy-les-Moulineaux, 9 déc. 2014

Y. Kokar, T. Dubois, M. Hélard et M. Crussière

"Towards common broadcasting physical layer for future converged broadband/broadcast networks"

Open Event du projet Mcube, Orange Gardens, Issy-les-Moulineaux, 16 mai 2013

M. Crussière

**Transfert de technologie**

"Procédé de réduction de facteur de crête pour les signaux DVB-T2" Technique brevetée, support à l'intégration sur plateforme matériel d'un partenaire industriel, 2015 et 2017

R. Mounzer, M. Crussière et J.F. Hélard
**Consortium de normalisation** "Potential of MIMO technologies for Next Generation Handheld broadcasting systems"

Présentation plénière, meeting du TM NGH du consortium DVB, 22 oct. 2009

M. Crussière

5

RESPONSABILITÉS SCIENTIFIQUES, RAYONNEMENT

► Comités de lecture et de programmes

Membre de "IEEE Transactions on Broadcasting"

comités de "IEEE Transactions on Vehicular Technologies"

lecture de "IEEE Wireless Communication Letters"

revues "IEEE Communication Magazine"

"EURASIP Journal of Wireless Communications and Networking (JWCN)"

"Annals of Telecommunications"

Reviewer régulier depuis 2008, environ 5 papiers par an, toutes revues confondues.

Membre de "IEEE Global Communication Conference (Globecom)"

comités de TPC member depuis 2016

programme "IEEE International Symposium on Power Line Communications (ISPLC)"

TPC member depuis 2015

"IEEE International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC)"

TPC member depuis 2013

"IEEE International Wireless Communications and Networking Conference (WCNC)"

TPC member depuis 2011

Responsable de "IEEE International Workshop on Cross-Layer Design (IWCLD)"

comité de Responsable du programme technique (TPC Chair), 2011

programme 3e Édition de la conférence organisée à Rennes.

Comité de "Programme ANR, appels à projets génériques"

relecture de Expert pour le comité d'évaluation CE25 (Infrastructures hautes performances, Sciences et Technologies Logicielles)

2016-2017

► Jurys de thèse

J'ai eu l'occasion de participer aux jurys de thèse mentionnés ci-après en tant qu'examineur.

Slim "Gestion des Interférences Pour les Réseaux de Femtocells en se basant sur les Techniques MIMO coopératives"

Soutenue le 29 nov. 2012

Ahmad "Optimisation et analyse des réseaux intelligents et des réseaux hétérogènes"

JABBAN Soutenue le 16 sept. 2013

Dinh-Thuy "Retournement temporel : application aux réseaux mobiles"

PHAN-HUY Soutenue le 14 déc. 2015
# 5. Responsabilités scientifiques, Rayonnement

## ▶ Responsabilités administratives et collectives

Enfin, depuis quelques années, je me suis impliqué dans la participation et la prise en charge de responsabilités d'ordre administratives sur le plan de la recherche, telles que celles données ci-dessous.

**Depuis** **Responsable de l'équipe SYSCOM**

**janvier 2017** Missions : coordination/animation scientifique, gestion administrative, suivi des indicateurs et de la communications, représentation.

**Membre nommé au conseil scientifique plénier de l'IETR**

**De 2014** **Membre élu au conseil de laboratoire de l'IETR**

**à 2016** Représentant du collège MCF

**Depuis 2010** **Membre nommé au comité de sélection section 63 de ENIB**

Membre externe, participation à la commission de recrutement d'un MCF en 2011

**Membre nommé au comité de sélection section 63 de l'INSA de Rennes**

Membre interne, participation à la commission de recrutement d'un MCF en 2009
Dans ce chapitre est répertoriée l'intégralité de mes publications classées par catégories : revues, conférences internationales et nationales, brevets et chapitres d'ouvrages.

► Revues internationales

[R.1] Ali Cheaito, Matthieu Crussière, Jean-François Hélard, and Yves Louët. "Quantifying the memory effects of power amplifiers : EVM closed-form derivations of multicarrier signals". *IEEE Wireless Communications Letters*, 6(1):34-37, 2017.

[R.2] Ali Cheaito, Jean-François Hélard, Matthieu Crussière, and Yves Louët. "EVM derivation of multicarrier signals to determine the operating point of the power amplifier considering clipping and predistortion". *EURASIP Journal on Wireless Communications and Networking*, 2016(1):281-292, 2016.

[R.3] Pape Abdoulaye Fam, Stéphane Paquelet, Matthieu Crussière, Jean-François Hélard, and Pierre Brétilton. "Analytical derivation and optimization of a hybrid unicast-broadcast network for linear services". *IEEE Transactions on Broadcasting*, 62(4):890-902, 2016.

[R.4] Hua Fu, Matthieu Crussière, and Maryline Hélard. "BER analysis for equal gain transmission in downlink multiuser MIMO systems". *Wireless Communications Letters*, IEEE, 4(5):533-536, 2015.

[R.5] Ming Liu, Jean-François Hélard, Maryline Hélard, and Matthieu Crussière. "Towards the next generation video broadcasting : Improved performance using distributed MIMO". *Wireless Personal Communications*, 84(4):2635-2649, 2015.

[R.6] Samar Sindian, Jean-François Hélard, Abed Ellatif Samhat, Matthieu Crussière, and Ayman Khalil. "Resource allocation mechanism in IEEE 802.15.3 parent/child model". *Wireless Networks*, 21(6):1863-1877, 2015.

[R.7] Samar Sindian, Matthieu Crussière, Jean-François Hélard, Abed Ellatif Samhat, and Ayman Khalil. "Admission control and resource allocation strategies for IEEE 802.15.5". *EURASIP Journal on Wireless Communications and Networking*, 2014(1):1-22, 2014.

[R.8] Matthieu Crussière, Catherine Douillard, Christian Gallard, Marie Le Bot, Benjamin Ros, Arnaud Bouttier, and Alain Untersee. "A unified broadcast layer for horizon 2020 delivery of multimedia services". *Broadcasting, IEEE Transactions on*, 60(2):193-207, 2014.

[R.9] Ming Liu, Matthieu Crussière, Maryline Hélard, and Jean-François Hélard. "Achieving low-complexity maximum-likelihood detection for the 3D-MIMO code". *EURASIP Journal on Wireless Communications and Networking*, 2014(1):1-16, 2014.

[R.10] Samar Sindian, Ayman Khalil, Abed Ellatif Samhat, Matthieu Crussière, and Jean-François Hélard. "Resource allocation in high data rate mesh WPAN : a survey paper". *Wireless personal communications*, 74(2):909-932, 2014.

[R.11] Thierry Dubois, Maryline Hélard, Matthieu Crussière, and Cécile Germond. "Performance of time reversal precoding technique for MISO-OFDM systems". *EURASIP Journal on wireless communications and networking*, 2013(1):1-16, 2013.

[R.12] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Cross-layer multiple-access optimization scheme for linear precoded OFDM UWB systems". *annals of telecommunications-annales des télécommunications*, 68(5-6):287-298, 2013.

[R.13] Ming Liu, Maryline Hélard, Matthieu Crussière, and Jean-François Hélard. "Distributed MIMO coding scheme with low decoding complexity for future mobile TV broadcasting". *Electronics letters*, 48(17):1079-1081, 2012.
[R.14] Ming Liu, Matthieu Crussière, and Jean-François Hélard. "A novel data-aided channel estimation with reduced complexity for TDS-OFDM systems". Broadcasting, IEEE Transactions on, 58(2):247-260, 2012.

[R.15] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Adaptive self-learning resource allocation scheme for unlicensed users in high-rate uwb systems". Wireless Personal Communications, 56(3):611-623, 2011.

[R.16] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Cross-layer resource allocation scheme under heterogeneous constraints for next generation high rate WPAN". International Journal of Network Security & Its Applications (IJNSA), 2(3):18-34, 2010.

[R.17] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Time-frequency spectrum sharing scheme for next generation OFDM systems". EURASIP Journal on Wireless Communications and Networking, 2010:116, 2010.

[R.18] Antoine Stephan, Emeric Guéguen, Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Optimization of linear precoded ofdm for high-data-rate UWB systems". EURASIP Journal on Wireless Communications and Networking, 2008:10, 2008.

[R.19] Youssef Nasser, J-F Hélard, and Matthieu Crussière. 3d mimo scheme for broadcasting future digital tv in single-frequency networks. Electronics Letters, 44(13):829-830, 2008.

[R.20] Youssef Nasser, J-F Hélard, and Matthieu Crussière. "System level evaluation of innovative coded MIMO-OFDM systems for broadcasting digital TV". International Journal of Digital Multimedia Broadcasting, 2008, 2008.

[R.21] Jean-Yves Baudais and Matthieu Crussière. "Resource allocation with adaptive spread spectrum OFDM using 2D spreading for power line communications". EURASIP Journal on Advances in Signal Processing, 2007(1):1-13, 2007.

[R.22] Emeric Guéguen, Nadia Madaoui, Jean-François Hélard, and Matthieu Crussière. "Combination of OFDM and CDMA for high data rate UWB". Comptes Rendus Physique, 7(7):774-784, 2006.

[R.23] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Adaptive spread-spectrum multicarrier multiple-access over wirelines". Selected Areas in Communications, IEEE Journal on, 24(7):1377-1388, 2006.

[R.24] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Loading algorithms for adaptive SS-MC-MA systems over wireline channels: comparison with DMT". European transactions on telecommunications, 17(6):659-669, 2006.

► Conférences internationales

[C.1] Pape-Abdoulaye Fam, Matthieu Crussière, Stéphane Paquelet, Jean-François Hélard, and Pierre Brétillec. "Energy efficiency of hybrid unicast-broadcast networks for mobile TV services". In Personal, Indoor, and Mobile Radio Communication (PIMRC), 2017 IEEE 28th Annual International Symposium on, page 6. IEEE, 2017.

[C.2] Ali Cheaito, Mohamed Saad-Farah, Matthieu Crussière, Jean-François Hélard, and Yves Louët. "Spectral analysis of predistorted non-linear amplified multicarrier signals". In Wireless Communications and Networking Conference (WCNC), 2017 IEEE, page 6. IEEE, 2017.

[C.3] Mohamad Zalghout, Samih Abdul-Nabi, Ayman Khalil, Maryline Hélard, and Matthieu Crussière. "Optimizing context-aware resource and network assignment in heterogeneous wireless networks". In Wireless Communications and Networking Conference (WCNC), 2017 IEEE, page 6. IEEE, 2017.

[C.4] Ferdaouss Mattoussi, Gheorghe Zaharia, Jean-François Hélard, and Matthieu Crussière. "Analytical modeling of losses in FDP protocol of HbbTV based push-VOD services over DVB networks". In Wireless Communications and Networking Conference (WCNC), 2017 IEEE, page 6. IEEE, 2017.

[C.5] Ali Mokh, Maryline Hélard, and Matthieu Crussière. "Extended receive antenna shift keying". In Telecommunications (ICT), 2017 International Conference on, page 5. IEEE, 2017.
[C.6] Mohamad Zalghout, Jean-François Hélard, Ayman Khalil, Samih Abdul-Nabi, and Matthieu Crussière. "Load-aware power efficiency maximization in heterogeneous wireless networks". In *Telecommunications (ICT), 2017 International Conference on*, page 7. IEEE, 2017.

[C.7] Ferdaouss Mattoussi, Jean-François Hélard, Gheorghe Zaharia, and Matthieu Crussière. "A reliable delivery of HbbTV based push-VoD services over DVB networks using RS codes". In *Broadband Multimedia Systems and Broadcasting (BMSB), 2017 IEEE International Symposium on*, page 5. IEEE, 2017.

[C.8] Krishna Chaitanya Bulusu Sri Satish, Matthieu Crussière, Jean-François Hélard, Ralph Mounzer, and Youssef Nasser. "A low latency algorithm for efficient PAPR reduction for DVB-T2 and ATSC 3.0 broadcast". In *Broadband Multimedia Systems and Broadcasting (BMSB), 2017 IEEE International Symposium on*, page 5. IEEE, 2017.

[C.9] Antoine Rozé, Matthieu Crussière, Maryline Hélard, and Charlotte Langlais. "Comparison between a hybrid digital and analog beamforming system and a fully digital massive MIMO system with adaptive beamsteering receivers in millimeter-wave transmissions". In *Wireless Communication Systems (ISWCS), 2016 International Symposium on*, pages 86–91. IEEE, 2016.

[C.10] Ferdaouss Mattoussi, Matthieu Crussière, and Jean-François Hélard. "HbbTV based Push-VOD services over DVB networks : Analysis and AL-FEC code application". In *Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2016 8th International Congress on*, pages 414–419. IEEE, 2016.

[C.11] Ali Cheaito, Yves Louët, Matthieu Crussière, and Jean-François Hélard. "Optimal operating point of the power amplifier with respect to the EVM for TV broadcasting applications". In *Broadband Multimedia Systems and Broadcasting (BMSB), 2016 IEEE International Symposium on*, pages 1–4. IEEE, 2016.

[C.12] Ali Cheaito, Matthieu Crussière, Jean-François Hélard, and Yves Louët. "Energy-efficiency optimization of the high power amplifier for multicarrier systems : Analytical EVM derivation". In *Computer Communications Workshops (INFOCOM WKSHPS), 2016 IEEE Conference on*, pages 409–414. IEEE, 2016.

[C.13] Louis-Adrien Dufrene, Ming Liu, Matthieu Crussière, Jean-François Hélard, and Jean Schwoerer. "Blind repetitions for cellular-IoT : Performance analysis of combination mechanisms". In *Telecommunications (ICT), 2016 23rd International Conference on*, pages 1–6. IEEE, 2016.

[C.14] Pape-Abdoulaye Fam, Stéphane Paquelet, Matthieu Crussière, Jean-François Hélard, and Pierre Brétillon. "Optimal capacity of hybrid unicast-broadcast networks for mobile TV services". In *Broadband Multimedia Systems and Broadcasting (BMSB), 2016 IEEE International Symposium on*, pages 1–5. IEEE, 2016.

[C.15] Mohamad Zalghout, Ayman Khalil, Matthieu Crussière, Samih Abdul-Nabi, and Maryline Hélard. "SDRAN-based user association and resource allocation in heterogeneous wireless networks". In *Wireless Communications and Networking Conference Workshops (WCNCW), 2016 IEEE*, pages 296–302. IEEE, 2016.

[C.16] Ming Liu, Matthieu Crussière, and Jean-François Hélard. "improved physical layer for energy-efficient M2M communications over cellular networks". In *Software, Telecommunications and Computer Networks (SoftCOM), 2015 23rd International Conference on*, pages 264–268. IEEE, 2015.

[C.17] Pape-Abdoulaye Fam, Matthieu Crussière, Jean-François Hélard, Pierre Brétillon, and Stéphane Paquelet. "Global throughput maximization of a hybrid unicast-broadcast network for linear services". In *Wireless Communication Systems (ISWCS), 2015 International Symposium on*, pages 146–150. IEEE, 2015.

[C.18] Maryline Hélard, Matthieu Crussière, Jean-Christophe Prévotet, and Yvan Kokar. "Application of time reversal principles to wireless communications : from single user SISO to multiple-user large scale MIMO scenarios". In *Softcom 2015*, 2015.

[C.19] Antoine Rozé, Maryline Hélard, Matthieu Crussière, and Charlotte Langlais. "Millimeter-wave digital beamsteering in highly line-of-sight environments for massive MIMO systems". In *Wireless World Research Forum Meeting*, volume 35, 2015.

[C.20] Matthieu Crussière, Hua Fu, and Maryline Hélard. "Time reversal based beamforming for wireless communications : a theoretical analysis from moderate-scale to large-scale antenna systems". In *Communications and Networking (COMNET), 2015 5th International Conference on*, pages 1–6. IEEE, 2015.
[C.21] Antoine Rozé, Maryline Hélard, Matthieu Crussière, and Charlotte Langlais. "Linear precoder performance for massive MIMO systems in near LOS environments : Application to mmwave transmission". In *European Wireless 2015; 21st European Wireless Conference; Proceedings of*, pages 1–6. VDE, 2015.

[C.22] Ralph Mounzer, Matthieu Crussière, Youssef Nasser, and J-F Hélard. "Tone reservation based papr reduction technique with individual carrier power allocation for multiple peaks reduction". In *Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st*, pages 1–6. IEEE, 2015.

[C.23] Ali Cheaito, Jean-François Hélard, Matthieu Crussière, and Yves Louët. "Impact of clipping on evm of the predistorted non-linear amplified multicarrier signals". In *Wireless Communication Systems (ISWCS), 2015 International Symposium on*, pages 76–80. IEEE, 2015.

[C.24] Ralph Mounzer, Matthieu Crussière, Youssef Nasser, and Jean-François Hélard. "Individual carrier multiple peaks tone reservation based PAPR reduction algorithms". In *VTC2015-Spring Proceedings of IEEE Vehicular Technology Conference*, pages 1–6, 2015.

[C.25] Ali Cheaito, Matthieu Crussière, Yves Louët, and Jean-François Hélard. "EVM derivation for multicarrier signals : Joint impact of non-linear amplification and predistortion". In *Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st*, pages 1–6. IEEE, 2015.

[C.26] Thierry Dubois, Maryline Hélard, Pierre Siohan, Matthieu Crussière, Laurent Chapelain, and Bruno Jahan. "Efficient MISO system combining time reversal and ofdm/oqam". In *European Wireless 2014; 20th European Wireless Conference; Proceedings of*, pages 1–5. VDE, 2014.

[C.27] Hua Fu, Matthieu Crussière, and Maryline Hélard. "Partial channel overlay in moderate-scale MIMO systems using WH precoded OFDM". In *Telecommunications (ICT), 2014 21st International Conference on*, pages 16–21. IEEE, 2014.

[C.28] Jean-Christophe Sibel, Matthieu Crussière, and Jean-François Hélard. "Analysis of decoding failures of DVB-S2 LDPC codes". In *Vehicular Technology Conference (VTC Fall), 2014 IEEE 80th*, pages 1–6. IEEE, 2014.

[C.29] Papa Moussa Ndao, Maryline Hélard, Matthieu Crussière, and François Yven. "Channel shortening for OFDM systems : An improved algorithm in noisy environments". In *Ultra-WideBand (ICUWB), 2014 IEEE International Conference on*, pages 228–233. IEEE, 2014.

[C.30] Ralph Mounzer, Youssef Nasser, Matthieu Crussière, and Jean-François Hélard. "Power control optimization for tone reservation based PAPR reduction algorithms". In *Personal, Indoor, and Mobile Radio Communication (PIMRC), 2014 IEEE 25th Annual International Symposium on*, pages 97–102. IEEE, 2014.

[C.31] Jean-Christophe Sibel, Matthieu Crussière, and Jean-Fraçoi Hélard. "Modeling BP decoding error events with the LDPC codes of the DVB-S2 standard". In *Personal, Indoor, and Mobile Radio Communication (PIMRC), 2014 IEEE 25th Annual International Symposium on*, pages 902–907. IEEE, 2014.

[C.32] Jean-Christophe Prévotet, Yvan Kokar, Maryline Hélard, and Matthieu Crussière. "Implementation of a time revel MISO OFDM test-bed". In *Wireless World Research Forum*, 2014.

[C.33] Samar Sindian, Ayman Khalil, Abed Ellatif Samhat, Matthieu Crussière, and Jean-François Hélard. "Admission control and resource allocation in IEEE 802.15.5 HDR WPAN". In *Network of the Future (NOF), 2014 International Conference and Workshop on the*, pages 1–2. IEEE, 2014.

[C.34] Samar Sindian, Ayman Khalil, Abed Ellatif Samhat, Matthieu Crussière, and Jean-François Hélard. "Resource allocation with differentiation between RT and NRT traffic in IEEE 802.15.5". In *Mediterranean Electrotechnical Conference (MELECON), 2014 17th IEEE*, pages 39–44. IEEE, 2014.

[C.35] Ming Liu, Jean-François Hélard, Matthieu Crussière, and Maryline Hélard. "Cooperative distributed MIMO broadcasting : a promising solution to the 'mobile data tsunami' in 2020". In *Wireless World Research Forum WWRF# 31*, 2013.

[C.36] Nicolas Cornillet, Matthieu Crussière, and Jean-François Hélard. "Optimization of the energy efficiency of a hybrid broadcast/unicast network". In *Wireless Communications and Networking Conference Workshops (WCNCW), 2013 IEEE*, pages 39–44. IEEE, 2013.

[C.37] Hua Fu, Matthieu Crussière, and Maryline Hélard. "Spectral efficiency optimization in overlapping channels using TR-MISO systems". In *Wireless Communications and Networking Conference (WCNC), 2013 IEEE*, pages 3770–3775. IEEE, 2013.
[C.38] Ming Liu, Jean-François Hélard, Matthieu Crussiere, and Maryline Hélard. "Reduced-complexity maximum-likelihood decoding for 3D MIMO code". In *Wireless Communications and Networking Conference (WCNC), 2013 IEEE*, pages 4015–4020. IEEE, 2013.

[C.39] Imad Jamil, Samar Sindian, Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "A new distributed decision making scheme for the IEEE 802.15.3 parent/child model". In *Communications and Information Technology (ICCIT), 2013 Third International Conference on*, pages 256–261. IEEE, 2013.

[C.40] Samar Sindian, Abed Ellatif Samhat, Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Dynamic superframe size-based admission control in parent/child HR WPANs". In *Communications and Information Technology (ICCIT), 2013 Third International Conference on*, pages 314–319. IEEE, 2013.

[C.41] Ming Liu, Matthieu Crussière, Maryline Hélard, and Jean-François Hélard. "Distributed MIMO schemes for the future digital video broadcasting". In *Telecommunications (ICT), 2013 20th International Conference on*, pages 1–5. IEEE, 2013.

[C.42] Ming Liu, Maryline Hélard, Jean-François Hélard, and Matthieu Crussière. "A fast decodable full-rate STBC with high coding gain for 4×2 mimo systems". In *Personal Indoor and Mobile Radio Communications (PIMRC), 2013 IEEE 24th International Symposium on*, pages 677–681. IEEE, 2013.

[C.43] Thierry Dubois, Maryline Hélard, Matthieu Crussière, and Issam Maaz. "Time reversal applied to large MISO-OFDM systems". In *Personal Indoor and Mobile Radio Communications (PIMRC), 2013 IEEE 24th International Symposium on*, pages 896–901. IEEE, 2013.

[C.44] Thierry Dubois, Maryline Hélard, and Matthieu Crussière. "Time reversal in a MISO-OFDM system : Guard interval design, dimensioning and synchronisation aspects". In *WWRF29*, 2012.

[C.45] Nicolas Cornillet, Matthieu Crussière, and Jean-François Hélard. "On the hybrid use of unicast/broadcast networks under energy criterion". In *Personal Indoor and Mobile Radio Communications (PIMRC), 2012 IEEE 23rd International Symposium on*, pages 1256–1261. IEEE, 2012.

[C.46] Ming Liu, Matthieu Crussière, Maryline Hélard, Jean-François Hélard, and Youssef Nasser. "Enhanced mobile digital video broadcasting with distributed space-time coding". In *Communications (ICC), 2012 IEEE International Conference on*, pages 6971–6976. IEEE, 2012.

[C.47] Ming Liu, Matthieu Crussiere, and Jean-François Hélard. "Improved channel estimation methods based on PN sequence for TDS-OFDM". In *Telecommunications (ICT), 2012 19th International Conference on*, pages 1–5. IEEE, 2012.

[C.48] Roua Youssef, Maryline Hélard, Matthieu Crussière, and Jean-François Hélard. "Effect of relaying on coverage in realistic deployment scenarios". In *Telecommunications (ICT), 2012 19th International Conference on*, pages 1–5. IEEE, 2012.

[C.49] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Spectrum sharing optimization model for OFDMA systems under joint time and frequency constraints". In *Telecommunications (ICT), 2012 19th International Conference on*, pages 1–5. IEEE, 2012.

[C.50] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Spectrum sharing optimization model for multiuser linear-precoded OFDM UWB systems". In *Wireless Communications and Networking Conference (WCNC), 2012 IEEE*, pages 1467–1472. IEEE, 2012.

[C.51] Nicolas Cornillet, Matthieu Crussière, and Jean-François Hélard. "Performance of the DVB-T2 system in a single frequency network : Analysis of the distributed alamouti scheme". In *Broadband Multimedia Systems and Broadcasting (BMSB), 2011 IEEE International Symposium on*, pages 1–4. IEEE, 2011.

[C.52] Roua Youssef, Maryline Hélard, Matthieu Crussière, and Jean-François Hélard. "Distributed coding for OFDM-based transmission in cooperative broadcast networks". In *Cross Layer Design (IWCLD), 2011 Third International Workshop on*, pages 1–5. IEEE, 2011.

[C.53] Ayman Khalil, Rana Diab, Matthieu Crussière, and Jean-François Hélard. "time-frequency resource allocation optimization model for OFDMA systems". In *Cross Layer Design (IWCLD), 2011 Third International Workshop on*, pages 1–5. IEEE, 2011.

[C.54] Thierry Dubois, Matthieu Crussière, and Maryline Hélard. "On the use of time reversal for digital communications with non-impulsive waveforms". In *Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on*, pages 1–6. IEEE, 2010.
[C.55] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Interference-aware prioritized spectrum scheduling for MB-OFDM systems". In *Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium on*, pages 1242–1247. IEEE, 2010.

[C.56] Karima Ragoubi, Maryline Hélard, and Matthieu Crussière. "Low complexity channel shortening technique applied to MB-OFDM UWB systems". In *Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on*, pages 1–6. IEEE, 2010.

[C.57] Ming Liu, Matthieu Crussière, and Jean-François Hélard. "Enhanced two-dimensional data-aided channel estimation for TDS-OFDM". In *Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on*, pages 1–7. IEEE, 2010.

[C.58] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Distributed coexistence-aware channel allocation for future unlicensed high-rate WPAN". In *Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on*, pages 1–7. IEEE, 2010.

[C.59] Hassan Ali-Ahmad, Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "A joint distributed resource management and scheduling scheme for future UWB-based high-rate WPAN". In *Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on*, pages 1–8. IEEE, 2010.

[C.60] Karima Ragoubi, Maryline Hélard, and Matthieu Crussière. "Channel shortening for bit rate maximization in DMT communication systems". In *Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd*, pages 1–5. IEEE, 2010.

[C.61] Iulia Ivan, Philippe Besnier, Xavier Bunlon, Loïs Le Danvic, Matthieu Crussière, and M'hamed Drissi. "Influence of propagation channel modeling on V2X physical layer performance". In *Antennas and Propagation (EuCAP), 2010 Proceedings of the Fourth European Conference on*, pages 1–5. IEEE, 2010.

[C.62] Ming Liu, Matthieu Crussière, and Jean-François Hélard. "A combined time and frequency algorithm for improved channel estimation in TDS-OFDM". In *Communications (ICC), 2010 IEEE International Conference on*, pages 1–6. IEEE, 2010.

[C.63] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Multiuser service differentiated spectrum allocation scheme for high rate UWB systems". In *Wireless Communications and Networking Conference (WCNC), 2010 IEEE*, pages 1–6. IEEE, 2010.

[C.64] Iulia Ivan, Philippe Besnier, Matthieu Crussière, M'hamed Drissi, Lois Le Danvic, Mickael Huard, and Eric Lardjane. "Physical layer performance analysis of V2V communications in high velocity context". In *Intelligent Transport Systems Telecommunications, (ITST), 2009 9th International Conference on*, pages 409–414. IEEE, 2009.

[C.65] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Differentiated multiuser resource allocation scheme for multi-band UWB systems". In *Signal Processing Advances in Wireless Communications, 2009. SPAWC'09. IEEE 10th Workshop on*, pages 707–711. IEEE, 2009.

[C.66] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Dynamic cross-layer spectrum allocation for multi-band high-rate UWB systems". In *Multi-Carrier Systems & Solutions 2009*, pages 355–364. Springer Netherlands, 2009.

[C.67] Oudomsack Pierre Pasquero, Youssef Nasser, Matthieu Crussière, and Jean-François Hélard. "A joint channel and carrier frequency offset estimation based on spread pilot for future broadcasting systems". In *Multi-Carrier Systems & Solutions 2009*, pages 153–161. Springer Netherlands, 2009.

[C.68] Oudomsack Pierre Pasquero, Matthieu Crussière, Youssef Nasser, and Jean-François Hélard. "Efficient space code block code mimo channel estimation for future mobile video broadcasting". In *Wireless Communications and Networking Conference, 2009. WCNC 2009. IEEE*, pages 1–6. IEEE, 2009.

[C.69] Oudomsack Pierre Pasquero, Eddy Chollet, Matthieu Crussière, and Jean-François Hélard. "Efficient spread pilot based synchronization method for linear precoded ofdm systems". In *Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th*, pages 1–5. IEEE, 2009.

[C.70] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Cross-layer resource allocation scheme for multi-band high rate UWB systems". In *Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing : Connecting the World Wirelessly*, pages 314–319. ACM, 2009.
[C.71] Ming Liu, Matthieu Crussière, and Jean-François Hélard. "A novel iterative data-aided channel estimation for time domain synchronous OFDM". In *Signal Design and its Applications in Communications, 2009. IWSDA'09. Fourth International Workshop on*, pages 48–51. IEEE, 2009.

[C.72] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Spectrum allocation optimization scheme for heterogeneous multiuser UWB systems". In *Cross Layer Design, 2009. IWCLD'09. Second International Workshop on*, pages 1–6. IEEE, 2009.

[C.73] Ayman Khalil, Antoine Stephan, Matthieu Crussière, and Jean-François Hélard. "Multi-user cross-layer allocation design for LP-OFDM high data rate UWB systems". In *Wireless Communication Systems. 2008. ISWCS'08. IEEE International Symposium on*, pages 6–10. IEEE, 2008.

[C.74] Fahad Syed Muhammmad, Jean-Yves Baudais, Jean-François Hélard, and Matthieu Crussière. "A coded bit-loading linear precoded discrete multitone solution for power line communication". In *Signal Processing Advances in Wireless Communications, 2008. SPAWC 2008. IEEE 9th Workshop on*, pages 555–559. IEEE, 2008.

[C.75] Fahad Syed Muhammmad, Jean-Yves Baudais, Jean-François Hélard, and Matthieu Crussière. "Coded adaptive linear precoded discrete multitone over PLC channel". In *Power Line Communications and Its Applications, 2008. ISPLC 2008. IEEE International Symposium on*, pages 123–128. IEEE, 2008.

[C.76] Oudomsack Pierre Pasquero, Matthieu Crussière, Youssef Nasser, and Jean-François Hélard. "2D linear precoded OFDM for future mobile digital video broadcasting". In *Signal Processing Advances in Wireless Communications, 2008. SPAWC 2008. IEEE 9th Workshop on*, pages 476–480. IEEE, 2008.

[C.77] Youssef Nasser, Jean-François Hélard, and Matthieu Crussière. "Robustness of MIMO-OFDM schemes for future digital TV to carrier frequency offset". In *Broadband Multimedia Systems and Broadcasting, 2008 IEEE International Symposium on*, pages 1–4. IEEE, 2008.

[C.78] Youssef Nasser, Jean-François Hélard, and Matthieu Crussière. "Bit error rate prediction of coded MIMO-OFDM systems". In *Signal Processing Advances in Wireless Communications, 2008. SPAWC 2008. IEEE 9th Workshop on*, pages 181–185. IEEE, 2008.

[C.79] Oudomsack Pierre Pasquero, Matthieu Crussière, Youssef Nasser, and Jean-François Hélard. "A novel channel estimation based on spread pilots for terrestrial digital video broadcasting". In *Broadband Multimedia Systems and Broadcasting, 2008 IEEE International Symposium on*, pages 1–4. IEEE, 2008.

[C.80] Ming Liu, Matthieu Crussière, Jean-François Hélard, and Oudomsack Pierre Pasquero. "Analysis and performance comparison of DVB-T and DTMB systems for terrestrial digital TV". In *Communication Systems, 2008. ICCS 2008. 11th IEEE Singapore International Conference on*, pages 1399–1404. IEEE, 2008.

[C.81] Youssef Nasser, J-F Hélard, Matthieu Crussière, and Oudomsack Pasquero. "Efficient 3D space time space block code for future terrestrial digital TV". In *Signal Processing Advances in Wireless Communications, 2008. SPAWC 2008. IEEE 9th Workshop on*, pages 406–410. IEEE, 2008.

[C.82] Youssef Nasser, Jean-François Hélard, and Matthieu Crussière. "On the influence of carrier frequency offset and sampling frequency offset in MIMO-OFDM systems for future digital TV". In *Wireless Pervasive Computing, 2008. ISWPC 2008. 3rd International Symposium on*, pages 93–96. IEEE, 2008.

[C.83] Youssef Nasser, Jean-Fraç Hélard, Matthieu Crussière, and Oudomsack Pasquero. "Efficient MIMO-OFDM schemes for future terrestrial digital TV with unequal received powers". In *Communications, 2008. ICC'08. IEEE International Conference on*, pages 2021–2027. IEEE, 2008.

[C.84] Jean-François Hélard and Matthieu Crussière. "Bit error rate prediction of coded MIMO-OFDM systems". In *IEEE Symposium on Signal Processing Advances in Wireless Communications*, page 5, 2008.

[C.85] Jean-François Hélard, Matthieu Crussière, and Oudomsack Pierre Pasquero. "Efficient 3D space time space block code for future terrestrial digital TV". In *Symposium on Signal Processing Advances in Wireless Communications*, page 5, 2008.

[C.86] Emeric Guéguen, Matthieu Crussière, and Jean-François Hélard. "An OFDM-CDMA scheme for high data rate UWB applications". In *Vehicular Technology Conference, 2007. VTC2007-Spring. IEEE 65th*, pages 2905–2909. IEEE, 2007.
[C.87] Emeric Guéguen, Matthieu Crussière, and Jean-François Hélard. "Combination of OFDM and spread spectrum for high data rate UWB: optimization of the spreading length". In Ultra-Wideband, 2007. ICUWB 2007. IEEE International Conference on, pages 889-894. IEEE, 2007.

[C.88] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Improved throughput over wirelines with adaptive MC-DS-CDMA". In Spread Spectrum Techniques and Applications, 2006 IEEE Ninth International Symposium on, pages 143-147. IEEE, 2006.

[C.89] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Adaptive linear precoded DMT as an efficient resource allocation scheme for power-line communications". In Global Telecommunications Conference, 2006. GLOBECOM'06. IEEE, pages 1-5,+. IEEE, 2006.

[C.90] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "New loading algorithms for adaptive SS-MC-MA systems over power line channels: Comparisons with DMT". Multi-Carrier Spread-Spectrum, pages 327-336, 2006.

[C.91] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Robust and high-bit rate communications over PLC channels: a bit-loading multi-carrier spread-spectrum solution". In Power Line Communications and Its Applications, 2005 International Symposium on, pages 37-41. IEEE, 2005.

[C.92] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "A novel joint and iterative scheme for synchronization and channel estimation in MC-CDMA power line communications". In Vehicular Technology Conference, 2004. VTC2004-Fall. 2004 IEEE 60th, volume 3, pages 1723-1727. IEEE, 2004.

[C.93] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "New iterative time and frequency synchronization scheme for MC-CDMA systems over power line channels". In Spread Spectrum Techniques and Applications, 2004 IEEE Eighth International Symposium on, pages 315-319. IEEE, 2004.

[C.94] Matthieu Crussière, Jean-Marie Auffray, and Jean-François Hélard. "Comparison of STTCM over slow and fast rayleigh fading channels". In Signal Processing Advances in Wireless Communications, 2003. SPAWC 2003. 4th IEEE Workshop on, pages 249-253. IEEE, 2003.

## ► Conférences nationales

[N.1] Ali Cheaito, Jean-François Hélard, Yves Louët, and Matthieu Crussière. "expression analytique du spectre pour les signaux multiporteuses : Impact conjoint des non-linéarités de l'amplificateur de puissance et de la fonction de prédistorsion". In GRETSI 2017, 2015.

[N.2] Pape Abdoulaye Fam, Stéphane Paquelet, Matthieu Crussière, Jean-François Hélard, and Pierre Brétillon. "On the energy efficiency of hybrid unicast-broadcast networks for mobile TV services". In Journée Scientifique URSI-France 2016 Energie et Radiosciences, 2016.

[N.3] Ali Cheaito, Matthieu Crussière, Yves Louët, and Jean-François Hélard. "Expression analytique de l'EVM pour les signaux multiporteuses : Impact conjoint des non-linéarités de l'amplificateur de puissance et de la fonction de prédistorsion". In GRETSI 2015, 2015.

[N.4] Elias Najjar, Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. Allocation dynamique de ressource dans les systèmes ULB sous contrainte de qualité de service. In Conférence MajeSTIC 2009, pages 1-5, 2009.

[N.5] Jean-Yves Baudais and Matthieu Crussière. "Allocation MC-CDMA: augmentation des débits sur les lignes de transmission". In 20e colloque GRETSI sur le traitement du signal et des images, pages 735-738, 2005.

[N.6] Matthieu Crussière, Jean-Yves Baudais, and Jean-François Hélard. "Vers la transmission de données haut-débit par courant porteur en ligne". In Journées thématiques TIC-CITE, pages 423-432, 2003.

## ► Brevets

[P.1] Matthieu Crussière, Thierry Dubois, Maryline Hélard, and Dinh-Thuy Phan Huy. "Procédé et dispositif de communication radio pour antennes d'usager multiples / radio communication method and device for multiple user antennas". Technical report, Orange Labs, Brevet français publié le 26.04.2012 (N° FR1058688) / Brevet US publié le 28 juin 2016 (Patent 9,379,797).
[P.2] Matthieu Crussière, Jean-François Hélard, Ralpha Mounzer, and Youssef Nasser. "Procédé et dispositif de transmission d'un signal multiporteuse, programme et signal correspondants". Technical report, INSA de Rennes, Brevet français déposé le 07.05.2015 (N° FR1554085).

[P.3] Jean-François Hélard, Maryline Hélard, Matthieu Crussière, and Roua Youssef. "Procédé d'émission coopérative, signal, entité source, entité relais, procédé de réception, entité destinataire, système et programme d'ordinateur correspondants / method of cooperative emission, signal, source entity, relay entity, method of reception, destination entity, system and computer program corresponding". Technical report, INSA de Rennes, Brevet français publié le 06.03.2014 (N° FR1258203) / Brevet US publié le 3 sept. 2013 (Patent App. 14/425,555).

[P.4] Maryline Hélard, Matthieu Crussière, and Karima Ragoubi. "Procédé de réduction de longueur de canal, filtre et signal correspondants/method for reducing channel length and corresponding filter and signal". Technical report, INSA de Rennes, Brevet français publié le 1 mars 2010 (N° FR1050656) / Brevet US Patent publié le 2 juin 2015 (Patent App. 9,048,916).

## ► Chapitres d'ouvrage

[B.1] Jean-Yves Baudais and Matthieu Crussière. "MIMO Powerline Communications : Narrow and Broad-band Standards, EMC, and Advanced Processing", chapter 18 : 'Linear Precoding for Multicarrier and Multicast PLC', pages 493–530. CRC Press, 2014. ISBN : 978-146-6557-52-9.

[B.2] Christian Gallard, Jean-Luc Sicre, Matthieu Crussière, Catherine Douillard, and Gérard Faria. "Next Generation Mobile Broadcasting", chapter 9 : 'Universal DVB-3GPP Broadcast Layer, an Enabler for new Business in Mobile Broadcasting Landscape', pages 253–291. CRC Press, 2013. ISBN : 978-143-9898-66-6.

[B.3] Ayman Khalil, Matthieu Crussière, and Jean-François Hélard. "Ultra Wideband Communications : Novel Trends-System, Architecture and Implementation", chapter 14 : 'Cross-layer resource allocation for MB-OFDM UWB systems', pages 125–144. InTech, 2011. ISBN : 978-953-307-461-0.

[B.4] Oudomsack Pierre Pasquero, Matthieu Crussière, Youssef Nasser, Eddy Cholet, and Jean-François Hélard. "Digital Video", chapter 7 : 'A new waveform based on linear precoded multicarrier modulation for future digital video broadcasting systems', pages 125–144. InTech, 2010. ISBN : 978-953-7619-70-1.
Partie II

# Synthesis of the Research Works
<figure><img src="image_11.png" /></figure>
This second part of the manuscript provides the detailed description of my research activities from the beginning of my carrier. A particular classification of the work is proposed and explicit to highlight the main fields of application I have been addressing during the last ten years. A first chapter presents the spirit of this classification and gives a broad view on the research programs I have co-supervised. The following three chapters focus on the main contributions within each of the identified fields of research. Finally, the last chapter of this part provides a structured view of the future envisaged studies. The whole of this part is written in english to give a more international scope to the document.

## Outline

<table><tr><td>Chapter 5 : Overview and classification of the research activities</td><td>p.39</td></tr><tr><td>Chapter 6 : Optimization of wireless broadcast transmissions</td><td>p.43</td></tr><tr><td>Chapter 7 : Optimization of the wireless broadband access</td><td>p.75</td></tr><tr><td>Chapter 8 : Broadband / Broadcast convergence studies</td><td>p.113</td></tr><tr><td>Chapter 9 : Research perspectives</td><td>p.135</td></tr></table>
<figure><img src="image_12.png" /></figure>
> Highly organized research
> is guaranteed to produce nothing new.

> - Frank Herbert -

## 1 CLASSIFICATION

When starting writing such an activity overview document, one of the first question which quickly comes to mind of any researcher is undoubtedly: "what is the common denominator which is giving a sense to my work?". Everyone knows that the answer to such a question is not so simple to give, honestly. As any researcher, I have been conditioned by my 3 years of PhD work. As many young assistant professor, I have been working (with pleasure) during my first years on subjects which main directions were essentially proposed or driven by the Professors who gave me the chance to work with. As any researchers, I have been influenced by my readings, my encounters with others during conferences, workshops and project meetings. But also, as any researcher, I have worked on subjects which could be funded. As such, finding a purely homogeneous common thread exhaustively linking all the contributions of several years research is almost impossible, and even undesirable unless yielding a very large but possibly unclear or fuzzy picture of the work.

Then comes the more appropriate possibility of research activity classification, which amounts to find several themes in the research, gathering close works into a given topic. However the question arises as to which kind of classification: "should the contributions be sorted by fields of application ? by the used methodologies ? by the exploited theoretical tools ? or even chronologically?". A unique classification is definitely not possible, and a given classification choice may have the inconveniences of another classification advantages and vice-versa. However, research activities classification should at least allow to highlight relationships between several studies thereby helping quickly perceiving the specificities of the research work.

From the above considerations, I have eventually chosen not to be exhaustive in the detailed description of my research activities. From a broad view, my research studies take place at the level of signal processing and system optimization applied to communication networks. To provide a more accurate description, I have selected the most representative contributions, organized in the following three main themes :

1. Wireless broadcast transmissions

2. Wireless broadband access

3. Broadcast/broadband convergent networks

Such a classification can be regarded as "application" kind but also implicitly allows differentiating between various problem statements, tools and methods used in each category.

The first theme on broadcast systems takes as a basic constraint that such systems sustain unidirectional downlink transmission without any knowledge or feedback from the receiver ends. Such systems can be viewed as "point-to-area" systems. The main related problematics we have addressed are then at the level of waveform optimization for diversity exploitation and energy efficiency.

The second theme on wireless access deals with adaptive systems able to embed flexible mechanisms due to the existence of feedback capability (partial or not) from the end terminals. Such systems are typically centralized
"point-to-multipoint" systems. The main studies we have led are the design of multiple access schemes and the optimization of radio resource management between users.

The third theme consists in system level rather than physical layer investigations, however taking basis on the radio system design potentially provided by the latter two themes. In this area of research, a major concern is the research for accurate models accounting for the joint usage of "heterogeneous radio technologies". In our studies, we have specifically been interested in modeling hybrid networks made of dual broadcast/unicast modes and deriving the related performance metrics.

From 2007, I have progressively structured the major part of my research activities according to such a classification. In the following sections, a chronological overview of each topic is given while a more detailed scientific description is given in the following chapters upon selecting contributions.

## 2 OVERVIEW OF THE STUDIES

### 2.1 WIRELESS BROADCAST TRANSMISSIONS

#### ► Synchronization and channel Estimation for next generation digital TV [2007-2011]

Our studies on broadcast systems started with our involvement in a large european Celtic project at the end of 2006 named B21C. At that time, the second version of the digital video broadcasting standard for terrestrial digital television (DVB-T2) had just been released. New investigations were needed in the perspective of the next generation for hand-held reception (DVB-NGH). Through the work of Pr. J.F. Hélard, our research team was historically well recognized for its expertise in OFDM systems and MIMO systems which were central issues to address for DVB-NGH. We hence launched a PhD program (P.O. Pasquero) aiming at proposing novel robust and flexible synchronization and channel estimation algorithms for portable and mobile reception based on OFDM waveform combined with spread-spectrum techniques. We for instance proposed the concept of spread pilots, and showed its advantage in terms of flexibility and robustness in mobility scenarios.

Almost in parallel to this work, we built a regional project (MobileTVWorld) with industrial partners focusing on the optimization of mobile receivers for the chinese digital television standard (DTM-B). With this project, we launched a new PhD (M. Liu) to work on channel estimation aspects in the particular case of the TDS-OFDM (time-domain-synchronous OFDM) waveform used in the DTM-B standard. We especially proposed an original time-frequency turbo approach allowing for improved robustness against high mobility and long echoes, hereby solving one of the main limitation of the TDS-OFDM waveform. I incorporated in Appendix 3 the transaction paper we wrote to summarize our work on this topic.

#### ► Space-time coding for broadcast networks [2009-2013]

In the same context as previously exposed, we also started new investigations on the potential upgrade of broadcast system with multiantenna capabilities. Our main concern was the design of new space-time codes well suited for single frequency network deployments which are typical of broadcast networks. This work was led during the second part of the PhD program of P.O Pasquero around and went on with two post-docs in the framework of the ENGINE Celtic project from 2009 to 2012 and partly of the MCube ANR project from 2010 to 2013. A major output of our works, further detailed in Chap. 6, was the proposal of various double-layer space-time codes robust to power imbalance coming from distant broadcast transmitters. We proposed various versions of such novel codes taking joint advantage of full-rank space-time codes such as Golden codes for intra-cell coding and orthogonal codes such as Alamouti code for inter-site coding. We also worked on simplified quasi-ML decoding strategies to optimized matrix code structures for moderate complexity receivers. I got the opportunity, as a responsible of the MIMO task force of the B21C project to expose the results of our work during a technical meeting of the DVB consortium in 2009.

#### ► Energy efficiency of broadcast transmitters [2011-2017]

After the works achieved during the B21C and ENGINES projects, we decided to investigate an old but however not solved issue of OFDM systems, that is PAPR reduction. Indeed, the DVB-T2 standard turns out
## 2. Overview of the studies

to be the first standard enabling PAPR reduction through the reservation of dedicated subcarriers. However, no commercial use of such possibility was made due to poor performance and high complexity of the existing algorithms. Hence, in 2012 we launched a new study with the regional PAPRICA project on such topic. During the PhD of R. Mounzer which was launched in collaboration with Dr. Y. Nasser from the American University of Beirut (AUB) in Lebanon, we namely proposed new algorithms, one of which being pattented and offering the best performance/complexity trade-off compared to the existing algorithms of the literature. This work was recently pursued with a new project (GreenTEA) which aim is to further optimize our algorithms in the perspective of an implementation in commercial products. A more deep description of this work is proposed in Chap. 6.

With our investigations about PAPR reduction optimization, we came up with new research ideas on the wide subject of power efficiency of high power transmitters. Indeed, from a theoretical point of view, no tools are available to accurately predict the performance of a transmission system equiped with a non-linear amplifier and some algorithms fighting against such non-linearities, such as PAPR reduction or predistortion functions. In 2013, we thus took the opportunity of the CominLabs LABEX in Rennes to participate to a project proposal dedicated to energy efficiency optimization in communication networks. We could then fund a PhD program (A. Cheaito) dedicated to the derivation of theoretical energy efficiency performance metrics. Many new closed-forms have been proposed as detailed in Chap. 6. A new PhD program starting in october 2017 is expected to push further the theoretical models we started to develop. This aspect will be developped as perspectives in Chap. 9.

### 2.2 WIRELESS BROADBAND ACCESS

This area of research is historically the one around which the SYSCOM research team developped its activities and expertise from its creation in the late 1990s. At that time, the central topic of interest driven by Pr. J.F. Hélard, was the optimization of waveforms for spectral efficiency optimization and multiple access purpose, first using combined OFDM and CDMA techniques, and then extending them to space-time coding schemes. In particular, such expertise allowed the team to be involved in major european projects from 2002 to 2006 dealing with 4G and beyong 4G cellular system optimization such as the FP5-IST MATRICE and FP6-IST 4MORE project. During that period, I was myself leading my PhD work in the team on the optimization of spread-spectrum OFDM systems, but rather developping resource allocation mechanisms for wired transmission systems, namely Power Line Communications.

### ► Waveform design and resource allocation for wireless personal area networks [2007-2014]

As I joined the laboratory and the SYSCOM team as an assistant professor in 2007, I was already well integrated into the team and right in line with research activities. I could therefore rapidly take part in the supervising of PhD students. My first major involvements consisted in contributing to the set up of a new European FP7-IST project (OMEGA), dealing with the optimization of domestic networks based on multi-technology radio access. In parallel to this project, we also led system optimization studies for WPAN in collaboration with Orange Labs (Rennes). In this framework, I partly extended the work of my PhD on resource allocation optimization, however in the context of ultra-wide band communications applied to WPAN. Two PhD students, namely E. Gueguen and A. Khalil, were contributing to this study, at a pure physical layer level for the former and developping cross-layer resource allocation algorithms for the latter. With the work of E. Gueguen, we first proposed to incorporate a linear precoding component to the Multi-band OFDM physical layer of the IEEE 802.15.3a specifications. We hereby proved the advantage of the LP-OFDM (linear-precoded OFDM) solution in the WPAN context. With A. Khalil, we proposed various cross-layer allocation strategies and optimization problems aiming at judiciously assigning sub-bands to users, depending on QoS and priority indicators. A journal paper presenting our main results in this subject is available in Appendix 3. This work was then followed with a PhD program (S. Sindian) set up in collaboration with the International University of Lebanon (IUL). In this study, we extended the work of A. Khalil to integrate multi-hop capabilities of the 802.15.5a specifications for mesh WPAN.

### ► Spatial filtering and beamforming strategies for multi antenna systems [2009-2017]

This topic of research started around 2009 as an evolution of the previous studies on multi-antenna systems in the team, however addressing the topic with the angle of spatial dimension multiple access (SDMA) relying on
closed (or almost closed) loop MIMO systems. The rising interest in the scientific community for such idea even in cellular systems in which channel knowledge at the transmitter is hard to guarantee, was promising numerous new investigations and theoretical studies.

Hence, Pr. M. Hélard and me initiated a new research project, first starting with a Master Intership and then with the PhD program of T. Dubois. Our first studies were dedicated to time-reversal filters which can be viewed as the core foundation or basis of spatial filtering and beamforming schemes, as further explained in Chap. 7. We experimented time-reversal concepts applied to wireless communications and worked on the derivation of the theoretical performance of OFDM systems, mainly in single user scenarios. We thereby highlighted the frequency/spatial duality and green nature for such systems as more detailed in Chap. 7. This work was first funded through a collaborative work with Orange Labs (Issy-les-Moulineaux) and then pursued in the framework of the ANR Trimaran project from 2011 to 2014.

Encouraged by our first results, we also started a new PhD (H. FU) thanks to a ministerial grant obtained in 2011. In this study, we extended our work in the multiuser context and to other spatial filtering schemes, working on theoretical system capacity and bit error rate closed-form derivations. At that period was emerging the famous Massive MIMO paradigm, introduced by T. Marzetta around 2010, which can be easily connected with our investigations on time-reversal (see Chap. 7). In the PhD work of H. FU, we however chose to address realistic multiantenna system topologies with a reasonnable number of antennas (hence not massive).

The raise of the number of antennas in our models came with the PhD of A. Rozé which started in 2013 in the framework of the launch of the IRT-Bcom in Rennes. Massive MIMO was identified within the IRT as a priority subject in the perspective of the future 5G system elaboration, which allowed us to initiate collaborations. By virtue of the win-win strategy of deploying massive MIMO systems at higher frequency bands than conventional ones, we focused our studies on mm-wave transmissions. We then proposed spatial filters and interference mitigation mechanisms more suited to such frequency bands, namely taking advantage of the quasi-stable angular structure of the propagation channels. All the work achieved in this field of research have actually opened the door to many new subjects for future investigations as further detailed in Chap. 9.

## 2.3 BROADCAST/BROADBAND CONVERGENT NETWORKS (2010 – 2017)

Around 2010 started to emerged the first views of what could be the future 5th generation wireless communication systems. Among many trends, the idea of making existing network converge, or at least cooperate, was assumed of being one of the key evolution at the horizon 2020. After several projects in the field of broadcast system optimization, we found interesting to investigate in what extent a cooperation between broadcast and broadband networks could enable overall improvement in system efficiency. Hence we started such new investigations, first in the framework of the ANR MCube project which was set up in 2010 with the collaboration of broadcast and broadband network operators (Orange Labs, TDF) but also with chip manufacturers (DibCom). Our first study relied on a collaborative contribution with the project partners to define a unified physical layer for a common broadcast/broadband network operation (see Appendix 3). Complementary to that, we put efforts on the modeling and the performance evaluation of such hybrid network during the PhD of N. Cornillet. We derived first theoretical results in terms of statistical performance metrics. This work was then pursued with the PhD of P.A. Fam through a collaboration between TDF and IRT-Bcom. As detailed in 8, we derived closed-form expressions in terms of service capacity and energy efficiency leading to optimal operating regimes of the network. Such research field, relying on our expertise in both the broadcast and wireless access systems calls for many further investigations as exposed in our research perspectives in Chap. 9.
# Optimization of Wireless Broadcast Transmissions

## Chap. 6

> To regard old problems from a new angle, requires creative imagination and marks real advance in science.
> 
> - Albert Einstein -

### Selected Topics

As discussed in the previous chapter, a first major field of application of my research activities is related to the improvement of the performance of broadcast systems. Among the complete set of my contributions related to broadcast systems, I have chosen to highlight in this chapter the following three aspects of the work :

1. MIMO schemes for broadcast networks

2. Practical PAPR reduction design

3. Theoretical efficiency analysis of high power transmitters

## 1 MIMO SCHEMES FOR BROADCAST SYSTEMS

### 1.1 MOTIVATIONS

Since its formalization by Foschini and Telatar in the late 90s [Fos96, Tel99], the Multiple Input Multiple Output (MIMO) paradigm has been the subject of numerous researches and have known impressive advances during two decades of theoretical and technological studies from academia and industry. During the first 10 years following the V-Blast spatial multiplexing scheme demonstrated at Bell Labs in 1996, studies on MIMO concepts were almost exclusively dedicated to the optimization of space-time coding schemes with the idea of getting as much as possible from the promised spatial multiplexing and diversity gains [TSC98, TJC99, Ala98]. As a result, first space-time block codes (STBC) have been quite rapidly adopted in some first communication standards before 2010 for WiFi applications (802.11.n) and cellular networks (3G-HSPA). In the meantime, broadcast technologies were placing greater emphasis on the integration of multicarrier waveforms, high order constellations, powerful channel coding schemes and flexible specifications for multiple scenario network deployments. At that time, it was not clear within the broadcast community whether adopting MIMO technology would be a good strategy, since multiple antenna concepts are more suited for mobile receivers. Yet, the deployments of hand-held DVB applications (DVB-H) had been suffering a serious setback for about 10 years.

In this context, we took part in 2007 in the set up of a very large European project (B21C - Broadcast for the 21st Century). At that time, the second version of the DVB-T standard was in discussion and new investigations were asked concerning mobile broadcasting. The B21C project was actually constituting a contribution task force to the reflections engaged by the DVB consortium in the perspective of two new DVB standard releases, namely DVB-T2 and DVB-NGH (Next Generation Hand-held). The work done in the framework of this project should give a support for the conclusions and decisions within DVB. The aim was to study all the technological modules
<figure><img src="image_13.png" /><figcaption>**FIGURE 6.1**– Single Frequency Network (SFN) area with three transmitters.</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>**FIGURE 6.2**– Composite channel impulse response in an SFN area with three transmitters.</figcaption></figure>

which may compose a future system. Particularly, we were involved in the project to analyze the potential of MIMO schemes and propose new solutions adapted to broadcast scenarios. In the sequel, I present the problem we addressed and the solution we proposed. This work was initiated with the PhD of O.P. Pasquero and then pursued with two Post-Docs.

## 1.2 CAPACITY OF OFDM-MIMO SYSTEMS IN SFN

### ► Broadcast SFN

One major particularity of broadcast networks is the possibility to operate some specific coverage areas with several transmit towers using a unique frequency band. In such a case, a same signal is sent from several different transmitters at the same time on the same carrier frequency. This is the concept of signal frequency networks (SFN) which represents a spectrally efficient implementation of radio coverage. Operating an SFN in a broadcast transmission scenario is natively possible because the same signal is strictly transmitted from the different towers of the network. Theoretically, it however contraints the transmitters of a same SFN area to be tightly synchronized. If OFDM is used, synchronization contraints are somehow relaxed thanks to the guard interval commonly used to absorb the multipath effects of propagation channels. Let us for instance consider the SFN case of two transmitters, as represented in Fig. 6.1. The equivalent channel impulse response viewed by a receiver in the overall coverage area of the SFN is represented in Fig. 6.2. It is simply interpreted as the superposition of two independent impulse responses with some potentially different delays and gains. Hence, any OFDM receiver can accomodate such a channel response as soon as the used guard interval remains larger than the overall delay spread of such composite channel<fnref n="1" />. When considering some MIMO upgrade of the network in the sequel, it is important to keep in mind the composite nature of the SFN channel.

### ► MIMO Capacity in SFN

From a system point of view, the SFN case implicitely poses the question of how to apply any space-time code across multiple antennas of the transmitters involved in the SFN area. As depicted in Fig. 6.3, one may think about a MIMO space-time code applied either at the level of the intra-cell antennas (co-localized STBC), or in a distributed fashion considering the inter-cell antennas (distributed STBC). Finally, a mixture of intra and inter-cell space-time code can also be envisaged. This idea, which we will refer to as 3D-MIMO, will be developped in the following section.

We addressed the capacity analysis question in [C.35] and provided some evaluation of the SFN system capacity for various MIMO configurations. The starting point of the evaluation was to restate the received signal taking into account the composite channel model and the way to exploit the MIMO channel, differentiating between the intra-cell and inter-cell channel links. In the general case of J transmission sites in the SFN area,

<footnote n="1">1. This means that the guard interval setting should strongly depend on the inter-site distance. For instance, in the 16K mode of DVB-T2, a guard interval of about 1.8 µs is used corresponding to an inter-site distance of about 133 km.</footnote>
# 1. MIMO Schemes for Broadcast Systems

<figure><img src="image_15.png" /><figcaption>FIGURE 6.3– SISO and MIMO configurations and scenarios in an SFN.</figcaption></figure>

each transmitter being equipped with $N_T$ antennas and each receiver with $N_R$, we can write the received signal vector $Y(k) \in \mathbb{C}^{N_R \times 1}$ on the $k$th subcarrier of the OFDM spectrum as,

$$ Y_k = [\mathbf{H}_k^{(1)} \cdots \mathbf{H}_k^{(J)}]^T \begin{bmatrix} \Lambda^{(1)} \\ \vdots \\ \Lambda^{(J)} \end{bmatrix} \mathbf{X}_k \quad (6.1) $$

where $\mathbf{H}_k^{(j)}$ are the $N_R \times N_T$ channel matrices of flat fading coefficients for subcarrier $k$ associated to each of the transmission sites, and $\Lambda^{(j)} = \sqrt{\lambda_j} \mathbf{I}_{N_T}$ are the power scale matrices taking into account the various levels of power associated to the signals received from different sites due to different propagation distances. Note that this system model considers a common signal $\mathbf{X}_k \in \mathbb{C}^{N_T \times 1}$ transmitted from each site, thus corresponding to the directly applying SFN concepts to MIMO signals.

We may rather take into consideration some distributed MIMO scheme, that is assuming that the transmitters collaborate and are responsible for the transmission of different information symbols. In that case, we have to rewrite Eq. (6.1) to differentiate between the transmitted signal from each site,

$$ Y_k = [\mathbf{H}_k^{(1)} \cdots \mathbf{H}_k^{(J)}]^T \begin{bmatrix} \Lambda^{(1)} & & 0 \\ & \ddots & \\ 0 & & \Lambda^{(J)} \end{bmatrix} \begin{bmatrix} \mathbf{X}_k^{(1)} \\ \vdots \\ \mathbf{X}_k^{(J)} \end{bmatrix} \quad (6.2) $$

From these two signal models, the capacity of the MIMO SFN system can be easily derived as reported in the following contribution Contrib. II.1.

## Contribution II.1 (Analytic Expression)

### Ergodic capacity of a MIMO-OFDM system in SFN

Given an SFN of $J$ transmitters of $N_T$ antennas each, a receiver with $N_R$ receive antennas, the OFDM-MIMO system capacities in the co-localized and distributed MIMO cases are

$$ \text{Co-localized} \quad C = \mathbb{E} \left\{ \frac{1}{N} \sum_{k=1}^{N} \log_2 \left( \det \left[ \mathbf{I}_{N_R} + \frac{P}{NN_T \sigma_n^2} \left( \sum_{j=1}^{J} \lambda_j \mathbf{H}_k^{(j)} \mathbf{H}_k^{(j)H} + \sum_{j \neq i} \sqrt{\lambda_i \lambda_j} \mathbf{H}_k^{(j)} \mathbf{H}_k^{(i)H} \right) \right] \right) \right\} \quad (6.3) $$

$$ \text{Distributed} \quad C = \mathbb{E} \left\{ \frac{1}{N} \sum_{k=1}^{N} \sum_{j=1}^{J} \log_2 \left( \det \left[ \mathbf{I}_{N_R} + \frac{P \lambda_j}{NN_T \sigma_n^2} \mathbf{H}_k^{(j)} \mathbf{H}_k^{(j)H} \right] \right) \right\} \quad (6.4) $$

where $P$ is the transmit power of each site and $0 \le \lambda_j \le 1$ is the power scale factor due to path-loss from transmit site $j$ such that $\sum_{j=1}^{J} \lambda_j \le 1$.

From this result, it is highlighted that the distributed approach translates into a spatial multiplexing capability of the SFN network, whereas the co-localized strategy rather implies a higher spatial diversity exploitation. However, in this latter case, note that the obtained diversity in not fully constructive due to the second summation
<figure><img src="image_16.png" /><figcaption>**FIGURE 6.4**– Channel capacity comparisons among several MIMO, SISO and SFN system strategies (Two transmitters).</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>**FIGURE 6.5**– Channel capacity gain of MIMO-SFN systems over SISO-SFN (Three transmitters).</figcaption></figure>

involving cross-talk terms (i.e. *jn*º*i*) in the composite SFN channel. This exactly reflects the behaviour of a pure SFN strategy in which a same signal is transmitted from different transmitters : the energy of the arriving signals is gathered by the OFDM receiver but do not necessarily in a constructive manner, yielding a more frequency selective channel. The hope is that coded OFDM can accomodate with such selectivity, which is in principle its main asset.

Using Eq. (6.3) and (6.4) in Contrib. II.1, it is then possible to plot some capacity curves in different scenarios. Note that we can get the SISO SFN case (corresponding to the actual broadcast network configuration) by setting $N_R = N_T = 1$. Also, we can obtain the single cell MIMO case by choosing $J = 1$, which essentially yields the well-known results on MIMO capacity [BGP02]. Fig. 6.4 shows some example of results for an SFN area of two transmitters with an inter-site distance of 10 km (the first site is at distance 0 km and the second site is at 10 km). The channel coefficients are considered as independent complex Gaussian processes and a simple path-loss model is used. We plot the capacity curves as a function of the distance of the receiver to the first transmitter for various system configurations. These curves are interesting to highlight the SFN effect which gives some coverage continuity in space compared to the single cell case. Also, we clearly see the benefit of MIMO strategies over the SISO case. Nonetheless, it is observed that the distributed MIMO case achieves higher spectral efficiency for all the user locations compared to the co-localized case.

In both cases, maximum capacity is obtained on each side of the curves when path-loss is minimized for one transmitter (i.e. $\sum_j \lambda_j = 1$). Contrary to that, the worst capacity values are obtained (SFN case) when the user is located right in between the two towers. However, the MIMO gain is preserved in such a situation, namely for the distributed case. The loss observed for the co-located case is due to the higher selectivity of the composite SFN channel as stated before. It is interesting to translate these results into capacity gain ($C_{MIMO}/C_{SISO}$), as done in Fig. 6.5 for the distributed case. The obtained gain turns out to be almost constant for all receiver location, except some slight boost at the boundaries of the cells, where indeed it is the most difficult in practice to maintain the quality of service.

## 1.3 ROBUST DISTRIBUTED STBC FOR SFN

### ► Power Imbalance Criterion

From the previous results, we can conclude that the distributed MIMO strategy is a straightforward extension and effective enhancement of the classical SFN scheme. The question that remains to be answered is however : which STBC is the most suited for SFN ? We already know from the capacity considerations that a distributed strategy is the best approach to follow. However, we have also understood that the composite SFN channel is
# 1. MIMO Schemes for Broadcast Systems

strongly changing owing to high path-loss variations according to the distance of the terminal to the transmitters of the SFN area. In the sequel, we will be referring to such a behaviour as power imbalance. Eventually, our question can be restated as : which STBC is the most robust to power imbalance ?

The capacity considerations of previous section are far from being sufficient to answer that question. They have to be completed with a system point of view integrating power imbalance effects. Even if distributed MIMO seems to be the best strategy, capacity results do not exhibit the fact that the same service (data content) has to be delivered whatever the location of the user. In that sense, using for example a simple distributed spatial multiplexing strategy would lead to some catastrophic situations. For instance, only half of the throughput would be received by a user close to one site and far for the other and the only favorable situation would be for a user with intermediate position between two transmitters. However, in a broadcast scenario, no consideration about receiving conditions can be taken. Hence, the design of a SBTC in the SFN broadcast context has to integrate power imbalance effects.

From the literature, power imbalance is usually not taken as a contraint in the STBC code design. The criteria stated by Tarokh and Calderbank [TSC98] suggest optimal space-time code construction based on the pair wise error probability minimization, on the channel capacity maximization or on the spatial diversity maximization. Many proposals emerged from 1999 to 2008 [WFGV98, TJC99, ZG02, Ion03, GH03, LV07, ZHG08], among which the most popular ones for a 2x2 MIMO topology : the Alamouti Code [Ala98] and the Golden code proposed by Belfiore [BRV05]. The former is an orthogonal code of unit spatial rate but it can extract the entire spatial diversity with linear processing. The latter is a full rate and full diversity, quasi-orthogonal code which achieves the optimal diversity/multiplexing gain tradeoff.

No explicit criterion has been stated in case of power imbalance between the entries of the spatial channel matrix. However we can easily understand that full rate codes as Golden code are expected to perform poorly if one of the spatial link is lost. Such codes are designed to maximize the spatial diversity with channel matrices of statistically balanced power for each entry. Such codes would then dramatically suffer any power imbalance. Contrary to that, the orthogonality criterion can be interpreted as a good criterion. With orthogonal codes, the data symbols transmitted from one antenna are also transmitted from the other antennas, after applying a judicious linear combination such that if any spatial link associated to one antenna vanishes (due to strong fading, or in our case due to strong path loss) the other spatial links still allow the symbol to be propagated to the receiver, without interfering with the other symbols (owing to the orthogonality criterion) and can hence be still recovered by the receiver. Hence, we can intuitively formulate that a good criterion for distributed STBC in SFN is to ensure orthogonality between the symbols transmitted from distant sites. This criterion will be referred to as "inter-site orthogonality criterion". It has been highlighted in [R.19]

## ► Double Layer STBC Proposal

According to the inter-site orthogonality criterion, we went to the idea of designing hierarchical STBC which construction is based on two levels of coding, namely an intra-site coding and an inter-site coding level. The idea is to apply an orthogonal structure to the inter-site coding layer to make the overall code robust to power imbalance. For the intra-site coding layer, any classical criterion can then be used because no power imbalance is experienced. Among the various possibilities we investigated, one of the most interesting one is the hierarchical Golden/Alamouti code introduced in [R.19]. This code, referred to as 3D-MIMO code, is specifically optimized for an SFN of two sites with two antennas per site and a receiver also equipped with two antennas. A corresponding illustration is given Fig. 6.6 highlighting the inter-cell coding based on Alamouti code and intra-cell coding based on Golden code.

<figure><img src="image_18.png" /><figcaption>FIGURE 6.6– Principle of the 3D-MIMO code as a 4x2 distributed STBC for an SFN with two transmitters.</figcaption></figure>
Contribution II.2 (System Design)

3D-MIMO code robust to power imbalance

Given an SFN of 2 transmitters with N<sub>T</sub> = 2 antennas each antennas, a robust distributed STBC of rate R = 2 is achieved with the following two-layer construction

$$
\text{Inter-site STBC} \quad \mathbf{X} = \begin{bmatrix} \mathbf{X}_1 & -\mathbf{X}_2^* \\ \mathbf{X}_2 & \mathbf{X}_1^* \end{bmatrix} \qquad (6.5)
$$

$$
\begin{align}
\text{Intra-site STBC} \quad \mathbf{X}_1 &= \frac{1}{\sqrt{5}} \begin{bmatrix} \beta(s_1 + \theta s_2) & \beta(s_3 + \theta s_4) \\ j\beta(s_3 + \bar{\theta}s_4) & j\beta(s_1 + \theta s_2) \end{bmatrix} \nonumber \\
\mathbf{X}_2 &= \frac{1}{\sqrt{5}} \begin{bmatrix} \beta(s_5 + \theta s_6) & \beta(s_7 + \theta s_8) \\ j\beta(s_7 + \bar{\theta}s_8) & j\beta(s_5 + \theta s_6) \end{bmatrix} \tag{6.6}
\end{align}
$$

with $s_i$ the input data symbols, $\theta = \frac{1+\sqrt{5}}{2}$, $\bar{\theta} = 1-\theta$, $\beta = 1+j(1-\theta)$ and $\bar{\beta} = 1+j(1-\bar{\theta})$.

By applying such a code, we ensure a full-diversity and non-vanishing coding gain if strong power imbalance
occurs, while maximizing the rate for the intracell coding. Indeed, from a capacity point of view, the inter-site
orthogonal structure leads to a constructive combination of the branches of the composite SFN channel. If we
were able to build a 3D code with an orthogonal inter-site layer whatever the number of transmitters in the
SFN, Eq. (6.4) would be transformed into,

$$
C = \mathbb{E} \left\{ \frac{1}{N} R_{\text{inter}} \sum_{k=1}^{N} \log_2 \left( \det \left[ \mathbf{I}_{N_R} + \frac{P}{NN_T \sigma_n^2} \frac{1}{R_{\text{inter}}} \left( \sum_{j=1}^{J} \lambda_j \mathbf{H}_k^{(j)} \mathbf{H}_k^{(j)H} \right) \right] \right) \right\} \quad (6.7)
$$

where $R_{inter}$ is the rate of the inter-site STBC. In this capacity expression, we can note that the SFN diversity
is fully exploited since the cross-talk terms in Eq. (6.4) are no more considered. This is an essential indication
about power imbalance robustness. The cost to pay for such robustness is the global spatial rate limitation due
to the orthogonality criterion which imposes $R_{inter} \le 1$ [TJC99, JH05]. Since 2x2 Alamouti is of rate $R_{inter} = 1$
and 2x2 Golden code is of rate $R_{intra} = 2$, the proposed 3D-MIMO code has a global spatial rate of $R = 2$.
Assuming a receiver with two antennas, the 3D-MIMO code is thus of maximal rate.

However, in a more general perspective of SFN areas composed of more than two transmitters, it becomes
impossible to build a two-layer STBC of rate R = 2 since there exist no orthogonal codes of rate R<sub>inter</sub> = 1 for
N<sub>T</sub> > 2. In the PhD of P. Pasquero, we studied various configurations with three transmitters and went to the
conclusion that the best deployment scenario was to keep the 3D-MIMO code. For the intra-site coding however,
many solutions are possible to address higher order MIMO topologies using 3x3 or 4x4 non-orthogonal STBC as
those proposed in [LC08] [SR13].

► Performance Analysis

In [R.19] and [C.41] we provided the main simulation results showing the superiority of the proposed code compared to other classical codes of the literature. We first identified the most important codes and MIMO strategies and established a list of these solutions as in Tab. 6.1. With the two-layer approach in mind, it is possible to understand the structure of many codes distinguishing between the intra-cell and the inter-cell coding, as done in the table. For example, it is seen that the Jafarkhani code [Jaf01] hierarchically encodes two Alamouti codes. Also, the L2 code [HH02] is seen as a variant.

Simulations have been launched using the complete DVB-NGH specifications using the DVB-NGH MIMO outdoor channel model [MPB11]. Such a model emulates a cross-polarized 2x2 MIMO transmission in UHF band and includes many propagation factors (multipath effects, Doppler shift, correlation among channel links). Fig. 6.7 first gives the obtained results when no power imbalance is considered for the different codes listed in Tab. 6.1. It clearly appears that the proposed 3D-MIMO codes outperforms all the other codes. Note that the SM 4x2 code corresponds to a special case of SFN co-localized MIMO (combinating SFN for inter-cell and spatial multiplexing for intra-cell). Interestingly such a code is not giving satisfying results as it could be expected from
# 1. MIMO Schemes for Broadcast Systems

<table><caption>TABLE 6.1– Summary if different space-time coding schemes applied to SFN.</caption><thead><tr><th>Category</th><th>ST scheme</th><th>Nb. of cells</th><th>N<sub>T</sub></th><th>N<sub>R</sub></th><th>Nb. of info. symb.</th><th>Nb. of time solts</th><th>Intra-cell ST coding</th><th>Inter-cell ST coding</th><th>ST decoding complexity<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="4">Classical solutions</td><td>SISO SFN</td><td>2</td><td>2</td><td>1</td><td>1</td><td>1</td><td>–</td><td>SFN</td><td>O(N)</td></tr><tr><td>MISO</td><td>2</td><td>2</td><td>1</td><td>2</td><td>2</td><td>–</td><td>Alamouti 2×1</td><td>O(N)</td></tr><tr><td>SIMO MRC</td><td>1</td><td>1</td><td>2</td><td>1</td><td>1</td><td>–</td><td>–</td><td>O(N)</td></tr><tr><td>MIMO</td><td>1 (or 2)</td><td>2</td><td>2</td><td>2</td><td>2</td><td>Alamouti (–)</td><td>– (Alamouti)</td><td>O(N)</td></tr><tr><td rowspan="3">Rate one</td><td>Jafarkhani</td><td>2</td><td>4</td><td>2</td><td>4</td><td>4</td><td>Alamouti</td><td>Alamouti</td><td>O(M<sup>4</sup>)</td></tr><tr><td>L<sub>2</sub> code</td><td>2</td><td>4</td><td>2</td><td>4</td><td>4</td><td>Alamouti-like</td><td>Alamouti</td><td>O(2M<sup>2</sup>)</td></tr><tr><td>Rate 1 Alamouti</td><td>2</td><td>4</td><td>2</td><td>2</td><td>2</td><td>Alamouti</td><td>SFN</td><td>O(M<sup>2</sup>)</td></tr><tr><td rowspan="3">Rate two</td><td>3D code</td><td>2</td><td>4</td><td>2</td><td>8</td><td>4</td><td>Golden</td><td>Alamouti</td><td>O(M<sup>8</sup>)</td></tr><tr><td>SM 4 × 2</td><td>2</td><td>4</td><td>2</td><td>2</td><td>1</td><td>SM 2 × 2</td><td>SFN</td><td>O(M<sup>2</sup>)</td></tr><tr><td>Rate 2 Alamouti</td><td>2</td><td>4</td><td>2</td><td>4</td><td>2</td><td>Alamouti</td><td>SM 2 × 2</td><td>O(M<sup>4</sup>)</td></tr></tbody></table>

<figure><img src="image_19.png" /><figcaption>FIGURE 6.7– Performance of distributed STBC schemes in the DVB-NGH outdoor MIMO channel without power imbalance. Doppler frequency is set to 33.3 Hz.</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>FIGURE 6.8– Performance of distributed STBC schemes in the DVB-NGH outdoor MIMO channel with power imbalance. Doppler frequency is set to 33.3 Hz.</figcaption></figure>

the capacity analysis in Fig. 6.4 when the receiver is at intermediate distance from the two transmitters. Then, Fig. 6.8 shows how the performance degrades when power imbalance occurs. The superiority and the robustness of the 3D-MIMO code is clearly confirmed against such power imbalance. Equivalent robustness is also noticed for all the other codes which are built upon orthogonal or SFN inter-cell strategy. Yet, as it could be expected, the code built upon inter-cell spatial multiplexing is dramatically degraded under the effect of power imbalance.

## 1.4 FAST DECODABLE DISTRIBUTED STBC

### ► Decoding Complexity Analysis

As demonstrated, the 3D-MIMO code outperforms all the other code of the literature considering an SFN system setting with two antennas per site and two antennas at the receiver. However, performance is not the only criterion to take into account for a solution to be chosen for practical implementation. Indeed, even if the inter-cell coding layer of our 3D-MIMO code is built upon an orthogonal structure, the overall resulting code is no more orthogonal. This means that optimal ML decoding can not be obtained through linear processing. The complexity of ML decoding is then directly depending upon the size of the search tree. The way to exhibit the complexity order of ML decoding of STBC is to rewrite the received signal following the approach in [BHV09]. The idea is to separate the real and imaginary parts of matrices and stacking them into vector forms,

$$Y = HX + W \rightarrow \tilde{y} = H_{eq}\tilde{s} + \tilde{w} \qquad (6.8)$$

<footnote>a The computational complexities required by the rate one and rate two ST coding schemes are the worst case searching times for each received symbol using sphere decoder. The searching space is associated to a given constellation size M.</footnote>
with $H_{eq}$ an equivalent channel matrix directly conditionned by the STBC structure. The equivalent channel matrix can then be QR decomposed, i.e. $H_{eq} = QR$, in order to get the ML solution of the transmitted symbols as,

$$ \hat{s} = \arg \min_{s \in \Theta^s} \|Q^T \hat{y} - R \hat{s}\|^2 \quad (6.9) $$

with $\Theta$ the set of constellation symbols, and $S$ the number of symbols involved in a STBC codeword. Hence, the ML solution is a joint search of $S$ information symbols of size $M$ resulting in a complexity of $O(M^S)^2$. As $8$ information symbols are involved in the structure of the proposed 3D-MIMO code, the obtained complexity becomes of order $O(M^8)$. The last column in Tab. 6.1 gives the related complexity orders for the other tested codes. As evident from these figures, our code exhibits the highest decoding complexity.

## Lowering the decoding complexity of the 3D-MIMO STBC

A first simple idea to work out the decoding complexity problem of the proposed code is to modify its structure in order to minimize the number of involved symbols. In other words, the aim was to obtain a more compact coding matrix. Hence, we built a new double layer STBC by re-arranging the Golden codewords following the Alamouti structure, but not proceeding to an hierarchical structure as made before. We finally went to a new version of the 3D-MIMO code viewed as a shorten one. Such code proposal has been introduced in [R.13] and is reported below.

### Contribution II.3 (System Design)

#### Shorten 3D-MIMO code

Given an SFN of 2 transmitters with $N_T = 2$ antennas each antennas, a robust distributed STBC of rate $R = 2$ is achieved with the following two-layer construction

$$ \text{Inter-site STBC} \quad \mathbf{X} = \frac{1}{\sqrt{2}} \begin{bmatrix} \mathbf{X}_1 & -\mathbf{X}_2^* \\ \mathbf{X}_2 & \mathbf{X}_1^* \end{bmatrix} \quad (6.10) $$

$$ \text{Intra-site STBC} \quad \mathbf{X}_1 = \frac{1}{\sqrt{5}} \begin{bmatrix} \beta(s_1 + \theta s_2) \\ j\bar{\beta}(s_3 + \bar{\theta}s_4) \end{bmatrix}, \quad \mathbf{X}_2 = \frac{1}{\sqrt{5}} \begin{bmatrix} \beta(s_3 + \theta s_4) \\ j\bar{\beta}(s_1 + \bar{\theta}s_2) \end{bmatrix} \quad (6.11) $$

with $s_i$ the input data symbols, $\Theta = \frac{1+\sqrt{5}}{2}$, $\bar{\Theta} = 1-\Theta$, $\beta = 1 + j(1-\Theta)$ and $\bar{\beta} = 1 + j(1-\bar{\Theta})$.

Since the Alamouti and the Golden code structures have been kept, the shorten version of the 3D-MIMO code is expected to provide good performance. But in addition to this, a straightforward complexity reduction from $O(M^8)$ to $O(M^4)$ is obtained. Furthermore, the Alamouti structure of the code allows for some further reduction of decoding complexity. Indeed, stacking the four transmitted and received complex symbols in a vector yields

$$ \underbrace{\begin{bmatrix} Y_1(1) \\ Y_2(1) \\ Y_1^*(2) \\ Y_2^*(2) \end{bmatrix}}_{y} = \underbrace{\begin{bmatrix} h_{11} & h_{14} & \cdots & h_{13} & h_{12} \\ h_{21} & h_{24} & \cdots & h_{23} & h_{22} \\ h_{13}^* & -h_{12}^* & \cdots & h_{11}^* & h_{14}^* \\ h_{23}^* & -h_{22}^* & \cdots & -h_{21}^* & h_{24}^* \end{bmatrix}}_{H} \underbrace{\begin{bmatrix} X_1(1) \\ X_2(1) \\ X_1(2) \\ X_2(2) \end{bmatrix}}_{x} + \underbrace{\begin{bmatrix} W_1(1) \\ W_2(1) \\ W_1^*(2) \\ W_2^*(2) \end{bmatrix}}_{w} = \quad (6.12) $$

where $X_k(n)$ denotes the coding symbol transmitted at antenna $k$ during symbol interval $n$. Hence, it clearly appears that the received symbols are generated through a channel matrix composed of two blocks. As the generator matrix of the Golden code is a block diagonal matrix [BRV05], we can show that the received symbol vector takes the following general form

$$ y = F_1 u + F_2 v + w \quad (6.13) $$

<footnote n="2">2. Note that lower decoding complexity may be achieved in practice through sphere decoding. Also some parallelisation can be processed by exploiting the orthogonality between information symbols. A correlation analysis between the information symbols can actually be acquired identifying the zero entries of matrix R [IFS13, SR09].</footnote>
# 1. MIMO Schemes for Broadcast Systems

with $\mathbf{u} = [s_1, s_2]^T$ and $\mathbf{v} = [s_3, s_4]^T$ and $\mathbf{F}_{1/2}$ some matrices depending on the channel coefficients and the Golden code generator matrix. From this equation, we can then think of applying some conditional ML algorithm. This is what we showed in more details in [R.13] and is summarized in the following algorithm.

## Contribution II.4 (Algorithm)

### Mixed ZF/ML decoding of the shorten 3D-MIMO code

A conditional ML solution to Eq. (6.13) is obtained as

$$ \hat{\mathbf{u}} = \arg \min_{\mathbf{u} \in \Theta^2} \|\mathbf{y} - \mathbf{F}_1 \mathbf{u} - \mathbf{F}_2 \hat{\mathbf{v}}(\mathbf{u})\|^2 \quad (6.14) $$

$$ \text{with, } \hat{\mathbf{v}} = Q(\tilde{\mathbf{v}}(\hat{\mathbf{u}})) $$

$$ \tilde{\mathbf{v}}(\mathbf{u}) = (\mathbf{F}_2^{\gamma} \mathbf{F}_2)^{-1} \mathbf{F}_2^{\gamma} (\mathbf{y} - \mathbf{F}_1 \mathbf{u}) $$

with $Q$ the hard decision function over the set of constellation symbols $\Theta$.

As a consequence to this proposal, the estimation of $\mathbf{v}$ is achieved through linear processing (ZF detection) and the $\mathbf{u}$ is decoded through a search over $\mathbb{M}^2$ combinations of information symbols leading to an overall complexity of $O(\mathbb{M}^2)$ instead of $O(\mathbb{M}^4)$ for the optimal ML algorithm. Hence, this conditional ML searching offers a trade-off between the ML and linear decoding methods.

## ► Performance and complexity trade-off analysis

A summary table of complexity evaluation is given in Tab. 6.2 for the proposed shorten 3D-MIMO with the ML and the conditional ML decoding strategies. Other promising codes of the literature are given for comparison purpose. It turns out that the proposed code needs the lowest decoding complexity among all rate-two codes to obtain ML solution. Note that the rate-one codes should use $\mathbb{M}^2$-QAM to achieve the same throughput as the rate-two ones with M-QAM. Therefore, the proposed code requires the same decoding complexity as rate-one codes to support the same system throughputs. Moreover, it needs least complexity among all STBCs considered if the conditional ML searching is employed.

Then moving to the performance results obtained in a DVB-NGH system setting, we give the curves of Fig. 6.9. As expected the proposed code exhibits a strong resistance to the power imbalance, even if about 0.5 dB performance degradation loss is experienced compared to the original 3D-MIMO code equal reception power

<table><caption>TABLE 6.2– Worst case decoding complexity of STBC.</caption><thead><tr><th>STBC</th><th>Rate</th><th>Complexity</th></tr></thead><tbody><tr><td>Short 3D-MIMO (ML)</td><td>2</td><td>O(M<sup>4</sup>)</td></tr><tr><td>Short 3D-MIMO (Cond. ML)</td><td>2</td><td>O(M<sup>2</sup>)</td></tr><tr><td>3D-MIMO</td><td>2</td><td>O(M<sup>8</sup>)</td></tr><tr><td>DjABBA [AHW07]</td><td>2</td><td>O(M<sup>7</sup>)</td></tr><tr><td>BHV [BHV09]</td><td>2</td><td>O(M<sup>6</sup>)</td></tr><tr><td>Srinath-Rajan [SR13]</td><td>2</td><td>O(M<sup>4,5</sup>)</td></tr><tr><td>Jafarkhani [JH05]</td><td>1</td><td>O(M<sup>2</sup>)</td></tr><tr><td>L2 [HH02]</td><td>1</td><td>O(M<sup>2</sup>)</td></tr></tbody></table>

<figure><img src="image_21.png" /><figcaption>FIGURE 6.9– Performance of distributed STBC schemes in the DVB-NGH outdoor MIMO channel with power imbalance. Doppler frequency is set to 33.3 Hz.</figcaption></figure>
between the transmitters of the SFN. Interestingly, the two codes have similar performance with high power imbalance. Then, the conditional ML solution suffers around 0.2 dB performance loss regarding the optimal ML decoding. We can also note that the BHV code has similar performance as the long 3D-MIMO code without power imbalance, but converges to the shorten 3D-MIMO performance when a transmission site is lost. We can then conclude that the proposed low complexity solution gives the best performance/complexity trade-off among the existing codes.

## 1.5 CONCLUSION

From 2007 to 2012, an important contribution of my work was at the level of the optimization of distributed STBC in the context of broadcast SFN. The 3D-MIMO and Shorten 3D-MIMO proposals have been two major outputs of this work. We participated during the B21C project to promote the idea of using Alamouti code structures for distributed coding in a SFN. Actually, a simple case of distributed MISO Alamouti (not detailed here) was part of the proposals made by different partners of DVB. The distributed MISO Alamouti code actually represents the first layer of the proposed 3D-MIMO code. Hence, in collaboration with other partners, we put some efforts providing some simulation results and analysis on this simple case, in order to prepare the promotion of the 3D-MIMO structure. As responsible of the MIMO task force within the B21C project, I had the opportunity to present the results of this work during a plenary DVB meeting in october 2009.

The simple distributed MISO solution has finally been confirmed as an option in the actual DVB-T2 specifications. Some field trials led by broadcast operators have recently shown the advantage of such simple technique. As far as the 3D-MIMO code is concerned, we tried to promote its concept during the ENGINES project in the perspective of the DVB-NGH elaboration. Due to complexity reasons, the solution finally retained for NGH is a simple mixture of localized Alamouti used in an SFN fashion. However, the basis of the 3D-MIMO code (first layer) is embedded in DVB. It is also the case for the newly released ATSC3.0 in USA. So, for these two actual standards, it might be a chance of possible extension to 3D-MIMO concepts for a future release.

### Summary (PhD/Dissemination/Projects)

- 1 PhD (P. Pasquero) and 2 Post-Doc (Y. Nasser, M. Liu)

- 4 international journal papers [R.5][R.9][R.13][R.19]

- 6 communications in internat. conf. and worksh. [C.35][C.38][C.41][C.42][C.81][C.82]

- 1 Contribution to DVB forum

- 2 projects (B21C, ENGINES)

## 2 PRACTICAL DESIGN OF PAPR REDUCTION ALGORITHMS

### 2.1 MOTIVATIONS

The last two decades have witnessed the generalization of multicarrier modulations in almost every communication standards, with in a pole position the world of TV broadcasting. It is however well-known that one of the main drawback of OFDM systems remains the high peak-to-average power ratio (PAPR) of the time domain signal which raises distortion and power efficiency issues at the amplification stage. It is indeed difficult to amplify OFDM signals without introducing any distortions (in band or out of band) using RF amplifiers since these latter are non-linear by nature, especially close to the saturation region. Also, limiting such distortions by backing off the signal power at the input of the amplifier in order to exploit the most linear region of its characteristics (far from the saturation region) leads to a dramatic loss of power efficiency (since it is maximum around the saturation point). Hence, for a given statistical distribution of the signal amplitude and for a given power
## 2. Practical design of PAPR reduction algorithms

amplifier characteristics, distortion mitigation and power efficiency increase appear as two adversarial problems. This situation is particularly critical in the case of high power amplifiers such as those used in broadcast networks which energy consumption is huge (in the order of several Megawatts for countries like France or Spain) and evaluated as being due to the power amplification of the signal for a ratio of about 80%.

Hence, a important field of my research of these last years at the level of broadcast systems was to find some solutions for the improvement of the energy efficiency of transmitters. Two well-known complementary strategies to counteract the above mentioned antagonism are on the one hand to work on the OFDM signal amplitude statistics modification, namely using PAPR reduction techniques, and on the other hand to compensate for the non-linearities of the power amplifier by means of linearization and predistortion techniques.

In the work described in this section, we have investigated the question of PAPR reduction. The objective of PAPR reduction is to decrease the fluctuations of the transmitted signal in order to exploit the PA at an operating point closer to the saturation region where its power efficiency is maximized. A huge amount of PAPR reduction algorithms have actually been proposed since 1990s (around 3500 hits in the IEEE Xplore database). Even though, it turns out that there exist today no practical algorithms able to offer a sufficient performance-complexity trade-off to be implemented in today's modulators. Hence, even if the topic of PAPR reduction in OFDM can be considered as an old subject widely addressed for years in the scientific community (and even at IETR), we decided to go a step further in the studies trying to understand the reasons of such a situation. During the european Celtic project B21C, some first studies allowed us to deal with the asymptotic performance it was possible to reach applying the TR concepts with infinite complexity. At the end of this project, we decided to set up a new project (PAPRICA) with one of the involved SME to specifically study and propose practical algorithms with implementation constraints. We naturally focused our attention upon tone reservation concept as it is already included in some digital broadcast standards (DVB-T2/NGH and ATSC3.0).

## 2.2 PAPR REDUCTION AND TONE RESERVATION ALGORITHMS

### ► State of the art

The objective of PAPR reduction is to decrease the fluctuations of the transmitted signal in order to exploit the PA at an operating point closer to the saturation region where its power efficiency is maximized. Various approaches and strategies have been suggested and studied as for example summarized in [HL05] [GEPB06] [KBP+12]. Clipping and filtering [LC98], coding [JWB94], partial transmit sequence [MH97] or selected mapping [BFH96], are the most popular reduction techniques. The main drawback of these methods is their high complexity with limited gain and the necessity to transmit, for some of them, side information to the receiver. In recent years, active constellation extension (ACE) [KJ03] and tone reservation (TR) techniques [TMoEE99] have been studied by many researchers because they are expected to offer the highest potential and do not need to transmit any side information. In particular, these two PAPR reduction techniques have been selected in various standards such as digital video broadcasting - second generation DVB-T2 [DT09], DVB for next generation handheld (DVB-NGH) and more recently the American digital video broadcasting standard ATSC 3.0 [ATS16].

### ► Tone Reservation Concept

The TR concept introduced by Tellado in [TMoEE99] relies on the dedicated usage of a subset of subcarriers for PAPR reduction purposes. This subset of so-called peak reduction tones (PRT) is used to generate a kernel signal in the time domain, added to the original one, and yielding a transmitted signal which has a lower PAPR than the original one<fnref n="3" />. To better understand the difficulty behind practical TR principles implementation, let us consider that we allocate *R* tones for PAPR reduction of the OFDM system of *N* subcarriers. We define *B* as the PRT subset of these *R* locations and *C* as the vector of *R* peak reduction symbols transmitted on these positions and zeros elsewhere. Similarly, let the complement set $B^c$ be the data tone subset of the useful data positions and *D* the vector of the *N* – *R* associated transmitted data symbols and zeros elsewhere. The resulting

<footnote n="3">3. Clearly, tone reservation does not degrade the BER performance of the system (at fixed $E_b/N_0$), since data subcarriers and PRT are orthogonal and can be naturally separated in the frequency domain at the receiver. Thus TR algorithms can be categorized as a downward compatible method [LP08].</footnote>
# Chapitre 6. Optimization of Wireless Broadcast Transmissions

<figure><img src="image_22.png" /><figcaption>FIGURE 6.10- Typical illustration of a TR scheme.</figcaption></figure>

signal to be transmitted can be represented in frequency and time domains as

$$X = C + D \quad \overset{\mathcal{F}}{\rightleftharpoons} \quad x = c + d \quad (6.15)$$
$$\text{where, } C = \begin{cases} C_k \neq 0, & \forall k \in \mathcal{B}, \\ C_k = 0, & \forall k \in \mathcal{B}^c, \end{cases} \quad \text{and, } D = \begin{cases} D_k \neq 0, & \forall k \in \mathcal{B}^c, \\ D_k = 0, & \forall k \in \mathcal{B}, \end{cases}$$

and with $\mathcal{F}$ standing for the discrete Fourier Transform. The illustration of such a model is given in Fig. 6.10. From this signal model, the PAPR of the baseband signal $x$, defined over a duration window corresponding to the OFDM symbol size, is then defined as follows,

$$\text{PAPR}_x = \frac{\|x\|_{\infty}^2}{\frac{1}{N} \|x\|_2^2} = N \frac{\|c+d\|_{\infty}^2}{\|c\|_2^2 + \|d\|_2^2}, \quad (6.16)$$

where $\|\cdot\|_{\infty}$ and $\|\cdot\|_2$ denote infinity and Euclidean norms, respectively.

From Eq. (6.15) and (6.16), we understand that the central issue is to design efficient algorithms able to compute, at each new symbol, the adequate $c$ (or equivalently the adequate values $C_k$ to load on the reserved tones) so as to efficiently reduce the PAPR. In addition, it can be understood that the power allocated to $c$ has to be limited in practice not to reduce the PAPR to the detriment of the useful power assigned to $d$. Hence, the search of the adequate $c$ shall respect some predefined power constraint.

## ► Theoretical optimization problem formulation

It is possible to state the TR optimization problem as a quadratically constrained quadratic program (QCQP) [TC98].

$$\begin{array}{ll}
\mathcal{P}_0: & \min_C \quad \|d + F^H\{C\}\|_{\infty}^2 \quad (6.17) \\
& \text{subject to,} \\
& \quad \|C\|_{\infty}^2 \le \frac{\Gamma}{N-R} \|D\|_2^2.
\end{array}$$

with $F$ the Fourier matrix. This problem essentially finds the optimal vector $C$ of complex values to associate to the PRTs so as to minimize the maximum peak value $\Lambda$ of the output signal. Note that the power constraint imposed on the reserved tones is a peak power constraint defined with respect to the power level associated to data tones. This corresponds to the case of DVB-T2/NGH and ATSC3.0 specifications, where the PRTs power boost $\Gamma$ shall be set to 10 dB maximum.

Indeed, Problem $\mathcal{P}_0$ can also be viewed as a special case of second order cone program (SOCP) [ZPLL06], which is a convex optimization problem class that minimizes a linear function over the intersection of an affine set and the product of second-order (quadratic) cones. Finding the optimal solution to $\mathcal{P}_0$ using SOCP requires very high computational complexity which completely prevents to implement such algorithm in practical transmitter.
## 2. Practical design of PAPR reduction algorithms

### 2.3 EXISTING PRACTICAL SOLUTIONS

Alternatively, the computation of the complex values $C_k$ assigned to the reserved tones can be computed iteratively. For instance, the DVB-T2, DVB-NGH and ATSC 3.0 broadcasting specifications include a gradient-based iterative algorithm for TR PAPR reduction. This solution, initially proposed in [JKE08] is based upon iteratively cancelling out the signal peaks by a set of impulse-like kernels. The reference kernel signal denoted as $κ$, is a Dirac-like pulse obtained by letting $C_k = 1, ∀k ∈ B$, that is

$$ κ = F^H\{1_{TR}\}, \quad \text{where, } 1_{TR} = \begin{cases} 1, & k \in B, \\ 0, & k \in B^c. \end{cases} \qquad (6.18) $$

From this kernel definition, one may understand that each peak of the time-domain signal can be mitigated or even cancelled by adequately shifting the original kernel $κ$ to make its peak position coincide with the detected one, and then scaling and subtracting the shifted kernel to reduce the signal peak amplitude$^4$. Hence, the QCQP optimization problem can be restated as follows,

$$ \mathcal{P}_1: \begin{array}{ll} \min_{\forall \rho_i, \forall \tau_i} & \left\| \mathbf{d} + \kappa \otimes \sum_{i=1}^{N_i} \rho_i \delta_N[n - \tau_i] \right\|_{\infty}^2 \\ \text{subject to,} & \|\mathbf{C}\|_{\infty}^2 \le \frac{\Gamma}{N-R} \|\mathbf{D}\|_2^2. \end{array} \qquad (6.19) $$

in which $⊗$ stands for circular convolution and $δ_N[n]$ is the Dirac delta discrete sequence vector of size $N$. In $P_1$, the search of the optimal solution translates into finding the optimal time delays $τ_i$ and weighting factors $ρ_i$, for a sufficient number of iterations $N_i$. The optimal resolution of $P_1$ leads to the same final solution as solving $P_0$. However, a suboptimal approach can be followed, by fixing $Lambda$ to a fixed reference value $\tilde{\Lambda}$ corresponding to the average value obtained in simulation by running the optimal resolution. Then, an iterative process can be established consisting in detecting the first highest peak, cancelling it, and then iteratively repeating the process for the other peaks. This iterative algorithm is schematically represented in fig. 6.11. The algorithm exits as soon as the power constraint is violated or when a predefined maximum number of iterations is reached.

As shown later on and published in [C.30][C.8], the gradient-based TR algorithm does not offer a sufficient performance-complexity trade-off to be implemented in today's DVB-T2 modulators. The major issue of this algorithm is its very slow convergence yielding a high number of iterations. A second issue is that it is inefficient in properly exploiting the available amount of power granted to the reserved tones. These last years, multiple researches have been focusing on enhancing the performance of TR gradient-based algorithms (e.g. [MNP+10a, MNP10b]). However, even if some improvements have been achieved, the proposed solutions do not sufficiently alleviate the convergence and power constraint issues for practical implementation.

### 2.4 PROPOSED ALGORITHM BASED ON NEW KERNEL DEFINITION

#### ▶ Comb-like kernel

The techniques introduced in this section are based on a new kernel definition and allocate power to the PRTs in order to benefit from all the amount of power available for PAPR reduction. We present a first algorithm referred to as Individual Carrier allocation for Multiple Peaks reduction (ICMP) and which offers a good performance/complexity tradeoff. Then, a second algorithm named Grouped ICMP (GICMP) is proposed in order to lower the latency of the previous one. Instead of a Dirac-type kernel as suggested by the DVB-T2 specifications, during the PhD of R. Mounzer [C.24], we came up with the idea of generating a comb-like kernel, associated to the activation of a single reserved tone at each iteration of the algorithm. The proposed kernel is then defined for each iteration $i$ as,

$$ v_i = F^H\{\mathbf{\Upsilon}^{(i)}\} \quad \text{with,} \quad \mathbf{\Upsilon}^{(i)} = \begin{cases} \mathbf{\Upsilon}_k^{(i)} = 1, & k \in \mathcal{B}(i) \\ \mathbf{\Upsilon}_k^{(i)} = 0, & \text{otherwise} \end{cases} \qquad (6.20) $$

<footnote n="4">4. This essentially amounts to modify the phase and the amplitude of the frequency domain complex values associated to the reserved tones.</footnote>
# Chapitre 6. Optimization of Wireless Broadcast Transmissions

<figure><img src="image_23.png" /><figcaption>FIGURE 6.11– Schematic representation of the TR gradient algorithm.</figcaption></figure>

The reason for such a choice is threefold. At first, allocating each reserved tone one by one allows to perfectly and implicitly control the power allocated to the tones. Then, the comb-like structure of the time domain kernel is expected to be able to reduce multiple peaks at a time since its energy is spread all over the OFDM symbol duration. The condition for that is to compute adequate phase-shift of the kernel as detailed hereafter. Last but not least, the kernel computation can directly be processed in time domain, without the use of any IFFT, since it is easily computed as follows

$$v_i(n) = \frac{1}{N} e^{-j\phi} e^{-j\frac{2\pi B(i)n}{N}}, \quad 0 \le k < N. \qquad (6.21)$$

## ► Related Optimization Problem

From this new kernel definition, we can state the modified optimization problem $\mathcal{P}_2$ as follows,

$$ \begin{array}{ll} \mathcal{P}_2: & \min_{\forall \rho_i, \forall \phi_i} \left\| \mathbf{d} + \sum_{i=1}^{N_i} \rho_i e^{j\phi_i} \mathbf{v}_i \right\|_{\infty}^2 \qquad (6.22) \\ & \text{subject to, } \quad \rho_i \le \frac{\Gamma}{N-R} \|\mathbf{D}\|_2^2. \end{array} $$

where it becomes obvious that the power constraint is easily controlled. Optimal resolution of problem $\mathcal{P}_2$ involves an intensive search of the optimal values $\rho_i$ and $\phi_i$. However, after thorough analysis of the optimal values obtained in simulations running the original QCQP algorithm on $\mathcal{P}_0$, it turns out that almost all reserved tones are loaded at the maximum allowed power level. Hence, a simplified sub-optimal problem can be obtained by fixing $\rho_i = A_{max}$, $\forall i$. Also, the search on the optimal $\phi_i$ values can be simplified by converting the infinite norm into a quadratic norm, but restricting the computation upon a given subset of time samples corresponding to the highest peak values of the OFDM signal. Hence, instead of minimizing the maximum peak amplitude (infinite
## 2. Practical design of PAPR reduction algorithms

norm criterion), we rather minimize the energy carried by multiple peaks above a given amplitude threshold (quadratic norm criterion). The corresponding optimization problem we have thus proposed states as,

$$ \mathcal{P}_3: \min_{\forall \phi_i} \left\| \mathbf{d}(S) + \sum_{i=1}^{R} A_{max} e^{j\phi_i} \mathbf{v}_i(S) \right\|_2^2 \quad (6.23) $$

$$ \text{subject to,} \quad \left\| \mathbf{d}(S^c) + \sum_{i=1}^{R} A_{max} e^{j\phi_i} \mathbf{v}_i(S^c) \right\|_{\infty}^2 \le \tilde{\lambda} $$

$$ \text{and,} \quad S = \{k : |d(k)| > \tilde{\lambda}\}. $$

where the threshold value $\tilde{\lambda}$ to use can be determined through simulations as in the gradient-based case.

### ► ICMP Algorithm

The crucial step in the resolution of Problem $\mathcal{P}_3$ is then the computation of the optimal phase $\phi_i$ of each comb-like Kernel $v_i$, which takes into account several peak positions (hence the name of the algorithm). As in the gradient-based case, a sub-optimal solution is used to solve the problem iteratively, i.e. computing the optimal phases $\phi_i$ sequentially. In such a case, the number of iterations equals the number R of available pilots. For one particular iteration $i$, assuming a given subset $S_i$ of detected peaks and a kernel $\text{upsilon}_i$ the optimal phase $\phi^*$ is obtained solving the following sub-problem,

$$ \mathcal{SP}_3: \min_{\phi} \left\| \mathbf{d}(S_i) + \mathbf{c}(S_i) \cdot A_{max} e^{-j\phi} \right\|_2^2. \quad (6.24) $$

Such a sub-problem involves a differential quadratic form which minimization is easy to obtain. After classical mathematical manipulations, the optimal phase $\phi_i^*(S_i)$ can then be expressed as,

$$ \phi_i^*(S_i) = \operatorname{atan} \left( \frac{\operatorname{Im}\{\mathbf{d}^H(S_i)\mathbf{v}_i(S_i)\}}{\operatorname{Re}\{\mathbf{d}^H(S_i)\mathbf{v}_i(S_i)\}} \right) - \frac{\pi}{2} \quad (6.25) $$

Eventually, the new tone reservation method we have proposed for reducing the PAPR of an OFDM signal is summarized hereafter and illustrated in Fig. 6.12. It has to be noticed that the proposed algorithm relies on quite low computation complexity. The $\tilde{\lambda}_i$ threshold may be adapted at each iteration to take into account the progressive PAPR reduction which is expected to occur along the iterations. These threshold values can be optimized in advanced through simulations.

### Contribution II.5 (Algorithm)

#### Individual Carrier allocation for Multiple Peaks reduction (ICMP)

From an initial time-domain OFDM symbol vector $\mathbf{d}$, the ICMP TR-based PAPR reduction algorithm applied on R reserved tones yields the following symbol vector :

$$ \mathbf{x} = \mathbf{d} + \mathbf{c} \quad \text{with,} \quad \mathbf{c} = A_{max} \sum_{i=1}^{R} \mathbf{v}_i e^{j\phi_i^*(S_i)} \quad (6.26) $$

where $\mathbf{v}_i$ is obtained from (6.21) and $\phi_i^*(S_i)$ is iteratively computed from (6.25) with $S_i$ the instantaneous subset of time-domain samples to consider at each iteration such that :

$$ S_i = \{k : |d(k) + A_{max} \sum_{j=1}^{i-1} \mathbf{v}_j(k) e^{j\phi^*(S_j)}| > \tilde{\lambda}_i\}. $$

with $\tilde{\lambda}_i$ a predefined amplitude threshold.

### ► GICMP Algorithm

With the proposed algorithm, the global latency, which is the most important criterion in PAPR reduction algorithm, is however proportional to the number of iterations and then to the number of PRTs. Since DVB-T2
# Chapitre 6. Optimization of Wireless Broadcast Transmissions

<figure><img src="image_24.png" /><figcaption>FIGURE 6.12- Iterative power allocation of the PRTs with ICMP in the frequency domain.</figcaption></figure>

and ATSC3.0 reserves 1% of the subcarriers for PAPR reduction, this would lead to a number of iterations raising from $R = 9$ in 2K mode to $R = 288$ in 32K mode. Since the latter mode it most likely to be deployment for terrestrial broadcast networks, ICMP it not yet suited to such a situation. To address this latency issue of the ICMP algorithm, we proposed to a new algorithm, namely GICMP, based on a grouping strategy of the PRTs. More precisely, the reserved pilots are grouped into G groups as follows

$$ \mathcal{B} = \{\mathcal{B}_1, \dots, \mathcal{B}_G\}, \qquad (6.27) $$

$$ \mathcal{B}_i = \{P_{1+\frac{(i-1)R}{G}}, \dots, P_{1+\frac{iR}{G}}\}, \text{ for } 1 \le i \le G. \qquad (6.28) $$

Then, one peaks search is executed per group with GICMP, instead of one per PRT with ICMP. The latency becomes then proportional to the number G of groups. The resulting GICMP algorithm is presented in the next contribution section on top of next page. With this final algorithm, the optimal phases associated to the PRTs of a same group are different but are computed in a parallel fashion based on a common peaks search to produce an aggregated kernel $v_g$ at each iteration. Hence, the latency, which is essentially driven by the peaks search process, can be substantially lowered since it becomes proportional to the number of groups<fnref n="5" />. One first counterpart of the parallel processing is the increase of the computation complexity of each iteration. A second one is the potential performance degradation, since the parallel phase computations avoid the possibility of taking into account any mutual effects occuring when summing up the kernels $v_{g+i}$ to form the aggregated kernel. Finally, a tradeoff between latency, performance and computational complexity has to be studied as addressed in the performance analysis of next section.

<footnote n="5">5. For instance, in the 32K OFDM mode of the DVB-T2 standard for which the number of PRTs is 288, one can use $G = 8$ groups of 36 PRTs.</footnote>
## 2. Practical design of PAPR reduction algorithms

### Contribution II.6 (Algorithm)

#### Grouped Individual Carrier allocation for Multiple Peaks reduction (GICMP)

From an initial time-domain OFDM symbol vector d, the GICMP TR-based PAPR reduction algorithm applied on G groups of R/G reserved tones yields the following symbol vector :

$$x = d + c \quad \text{with, } c = A_{\max} \sum_{g=1}^{G} \underline{v}_g \quad (6.29)$$

$$\text{and, } \underline{v}_g = \sum_{i=0}^{\frac{R}{G}-1} v_{g+i} e^{j \phi_{g+i}^*(S_g)}$$

where $v_{g+i}$ is obtained from (6.21) and $\phi_{g+i}^*(S_g)$ is iteratively computed from (6.25) however using $S_g$ the subset of time-domain samples constituted at each grouped iteration (i.e. for each group g) as :

$$S_g = \{k : |d(k) + A_{\max} \sum_{h=1}^{g-1} \underline{v}_h(k)| > \tilde{\lambda}_g\}.$$

## 2.5 PERFORMANCE RESULTS AND ANALYSIS

The proposed ICMP and GICMP algorithms have been patented in 2015 [P.2]. By then, many results on the proposed algorithms have been published, namely in [C.22], [C.24], and a journal paper has recently been submitted to IEEE Transactions on Broadcasting aiming at summarizing our work on new PAPR reduction algorithms including the measurement obtained on testbeds in the framework of the PAPRICA collaborative project led in collaboration with a device manufacturer.

In the following we give the main results in terms of performance and complexity of the proposed ICMP and GICMP algorithms. As QCQP yields optimal performance (at the price of huge computational complexity), it will be considered as the upper-bound in all the presented results. On the other hand, Gradient-based algorithm suggested by the DVB-T2 standard will be used as a benchmark for state-of-the art performance. Finally the original situation without any PAPR reduction will be given as lower-bound.

### Simulation conditions

The different simulations have been obtained using a baseband physical layer simulation chain which main parameters respect the DVB-T2 system specifications, namely at the level of the OFDM waveform [DT09]. More importantly, the location of the data and reserved tones have been set regarding the standard.

The different curves that will be providing in the sequel correspond to either CCDF (complementary cumulative distribution function) curves of the PAPR value, or MER (modulation error ratio) curves of the output signal after amplification. The definition of these two metrics are introduced hereafter.

CCDF of PAPR is actually the most commonly used metrics in the academic literature. However, a more practical figure of merit used in practice by device manufacturers and network operators is MER. MER quantifies the performance of a digital radio transmitter or receiver in a communication system using digital modulation. It is a direct measure of the signal quality taking into account the imperfections regarding practical implementation<fnref n="6" />. The MER computation consists in comparing the actual location of a received symbol vector to its ideal location.

<footnote n="6">6. The European Telecommunications Standards Institute (ETSI) defines the MER as one of the measurement guidelines for DVB systems [V1.01].</footnote>
# Chapitre 6. Optimization of Wireless Broadcast Transmissions

It is defined in dB as <fnref n="7" />,

$$ \text{MER}\{\mathbf{X}, \hat{\mathbf{X}}\} = 10\log_{10}\left(\frac{\|\mathbf{X}\|_2^2}{\|\mathbf{X} - \hat{\mathbf{X}}\|_2^2}\right). \qquad (6.30) $$

Focusing on the degradation due to non-linear amplification, X is the ideal symbol vector measured at the input of the amplifier and $\hat{\mathbf{X}}$ is measured at its output. Thus, MER gives an indication of the ability of the receiver to correctly decode the signal. Indeed, the MER metric gives additional insights compared to CCDF since it directly integrates the impact of the non-linearity of the power amplifier. Hence, we propose to widely consider the MER as the main parameter in quantifying the performance of PAPR reduction techniques. In addition, unlike CCDF of PAPR, MER is independent of the symbol length and then of the number of subcarriers [V1.01].

Measuring the MER however depends on both the power amplifier behavior and the power back-off applied to the signal at the input of the amplifier. As for the power amplifier we will consider in simulations the well-known Rapp model which is commonly used for solid-state HPAs which do not apply any phase change to the input signal [Rap91]. Such a model is governed by a so-called knee factor b revealing the smoothness of transition from the linear region to the saturation region (the lower b, the smoother the transition). In all the presented results, a knee factor b = 10 will be used, corresponding to a quite good predistorted amplifier approaching the so-called soft envelope limiter [Ol02b]. This choice is reasonable since practical implementations often embed predistortion techniques. In particular, this will be the case of the later introduced testbed used to validate our algorithms.

Using this model, we will measure the MER considering variable Input power Back-Off (IBO) values, yielding MER versus IBO curves. Since a larger IBO leads to a higher MER, these MER curves will be monotonously increasing with the IBO. Therefore, using these curves for performance comparison purpose will be easy : the upper the better the MER curves.

## ▶ ICMP and GICMP optimal settings

In this paragraph, we seek how to set the parameters of the proposed algorithms which still remain as degrees of freedom. As for the ICMP algorithm first, we have to find through simulations the optimal thresholds $\tilde{\lambda}_i$ to use at each iteration i to select the highest peaks in the time domain signal further used for the optimal phase computation $\phi_i^*$. After thorough analysis of the algorithm behaviour, we went to the conclusion that a constant threshold could be used across the iterations. Also, as the number of detected peaks directly impacts the computational complexity of the optimal phase computation, we led our simulations rather using parameter S defined as the number of selected peaks, i.e. $S = \text{Card}\{S\}$. Hence, by varying the size of S, the threshold level $\tilde{\lambda}$ is indirectly adjusted, but the impact on complexity is directly caught.

Fig. 6.13 gives the MER for a varying number S of selected peaks, and comparing the ICMP results with the reference curves previously identified. The power level of the PRTs is set to $\Gamma = 10$ dB above that of the data tones. It first turns out that the proposed algorithm clearly outperforms the state-of-the art gradient-based algorithm, even if the latter is run over a large number $N_i = 30$ of iterations. Then, making S vary, we are able to approach the optimal QCQP performance. As increasing S amounts to increase the computational complexity, an acceptable trade-off for the sequel will be to set $S = 100$ in 32K mode. In that case, targeting an MER of 34 dB, the proposed algorithm leads to a IBO reduction of about 0.5 dB compared to the original situation without PAPR reduction, and of about 0.3 dB compared to the gradient-based algorithm. The IBO could be further reduced of about 0.1 dB only if implementing the QCQP optimal solution were possible. On the other hand, with an IBO of 6.4 dB, the ICMP algorithm yields an MER gain of 2 dB compared to the gradient-based solution and almost 3 dB compared to the non PAPR reduction case.

Leading the same analysis for other OFDM modes yields the general conclusion that using between 2% and 3% of the samples (the highest peaks) is a good performance/complexity trade-off. Complementary results in terms of CCDF in 2K mode are given in Fig. 6.14 with $S = 5$ proving the superiority of the proposed algorithm compared to the gradient-based approach.

As ICMP is not adapted for the highest OFDM modes, let us now get the optimal settings for the GICMP algorithm. As ICMP and GICMP are based on the same concept, we will be using the same approach for the peak detection in the GICMP case as in the ICMP case. Hence, the rest of the simulations will be obtained with a fixed threshold, i.e. a fixed maximum peaks set size S, along the iterations. The particular parameter that has

<footnote n="7">7. Note that MER is closely related to the error vector magnitude, where the later can be defined as the square root of the former.</footnote>
## 2. Practical design of PAPR reduction algorithms

<figure><img src="image_25.png" /><figcaption>**FIGURE 6.13**– MER for a DVB-T2 system in 32K mode with ICMP : choice of the peaks subset size $S = cardS$. Power constraint is set to $\Gamma=10$ dB.</figcaption></figure>

<figure><img src="image_26.png" /><figcaption>**FIGURE 6.14**– CCDF of PAPR for DVB-T2 system in 2K mode. Comparison between QCQP, ICMP and Gradient-based algorithms. Power constraint is set to $\Gamma=10$ dB.</figcaption></figure>

<figure><img src="image_27.png" /><figcaption>**FIGURE 6.15**– MER for a DVB-T2 system in 32K mode with GICMP : choice of the number of groups $G$. Power constraint is set to $\Gamma=10$ dB.</figcaption></figure>

<figure><img src="image_28.png" /><figcaption>**FIGURE 6.16**– MER for a DVB-T2 system in 32K mode with GICMP : influence of the power constraint $\Gamma$. GICMP parameters are $S = 100$ and $G = 8$.</figcaption></figure>

to be optimized is however the number $G$ of PRTs groups. In that perspective, Fig. 6.15 gives the MER plots when $G$ varies from $G = 1$ (i.e. considering all the 288 PRTs once) to $G = 8$ (i.e. considering 8 iterations of 36 PRTs). It appears that GICMP almost converges to ICMP at $G = 8$ meaning that the performance degradation expected from the grouping and kernel aggregation approach becomes negligible. Then, the choice of $G$ only relies on complexity and latency considerations. In any case, we conclude that the proposed algorithm solves the latency issue identified as one of the major drawback of the gradient-based solution.

We finally provide additional results obtained when changing the power constraint $\Gamma$ applied to the PRTs. Fig. 6.16 gives the MER curves for the different algorithms for $\Gamma$ varying from 3 to 10 dB. Interestingly, the proposed GICMP algorithm yields quasi-optimal results at very tough power constraint, i.e. for 5 and 3 dB. This proves the ability of the proposed algorithm to accommodate for the power constraint contrary to the gradient-based solution.

### ► complexity/latency/performance analysis

In this paragraph, we give a synthetic view of the studied and proposed algorithms comparing their respective complexity, latency and performance. Table 6.3 summarized the main concluding points extracted from the simulations and preceding analyses.
# Chapitre 6. Optimization of Wireless Broadcast Transmissions

<table><caption>TABLE 6.3- Comparison analysis of different TR algorithms for DVB-T2 and ATSC 3.0.</caption><thead><tr><th>Criteria</th><th>DVB-T2 TR</th><th>QCQP</th><th>ICMP</th><th>GICMP</th></tr></thead><tbody><tr><th>Performance</th><td>Poor<br>---</td><td>Optimal<br>+++</td><td>Quasi-optimal<br>++</td><td>Quasi-optimal<br>++</td></tr><tr><th>Complexity</th><td>Very low<br>+++</td><td>Very high<br>---</td><td>Low<br>++</td><td>Medium<br>+</td></tr><tr><th>Latency</th><td>high<br>---</td><td>Very high<br>---</td><td>Medium<sup>†</sup><br>-/+</td><td>Low<br>+++</td></tr><tr><th>Real time kernel<br>generation</th><td>No<br>-</td><td>No<br>-</td><td>Yes<sup>††</sup><br>+</td><td>Yes<sup>††</sup><br>+</td></tr><tr><th>Efficient<br>power use</th><td>No<br>-</td><td>Yes<br>++</td><td>Yes<br>+</td><td>Yes<br>+</td></tr></tbody></table>

† : depends on the number of reserved tones

†† : Can be done with simple phase shift operations

<table><caption>TABLE 6.4- Average MER gain vs power levels.</caption><thead><tr><th></th><th>Class AB MER</th><th>Doherty MER</th></tr></thead><tbody><tr><td>No PAPR reduction</td><td>35.9 dB</td><td>37.0 dB</td></tr><tr><td>GICMP, PC=3 dB</td><td>37.5 dB (+1.6)</td><td>38.6 dB (+1.6)</td></tr><tr><td>GICMP, PC=5 dB</td><td>38.0 dB (+2.1)</td><td>39.0 dB (+2)</td></tr><tr><td>GICMP, PC=10 dB</td><td>38.2 dB (+2.3)</td><td>39.2 dB (+2.2)</td></tr></tbody></table>

For all the algorithms, latency is essentially due to the number of iterations needed to reach the optimal (QCQP) or yield satisfying results (gradient, ICMP, GICMP). It has to be understood that each iteration of each of the algorithms needs a complete scanning of the OFDM symbol under process (i.e. N clock cycles) for the detection of the maximum or set of maximum peaks. As a new OFDM symbol frame is expected to be output also every N clock cycles, PAPR reduction can be accomodated by the processing platform only if an overclock factor roughly equivalent to the number of iterations is used. Hence, the gradient-based algorithm leads to either a prohibitive number of iterations, or to very poor results. In classical ICMP, the number of iterations is equal to the total number of reserved subcarriers, while in GICMP it is equal to the number of groups. This explains the substantial decrease in the implementation latency.

As for the complexity, ICMP and GICMP algorithms turn out to be more complex than the gradient-based algorithm due to the optimal phase computation of Eq. (6.25) involving S complex values. This complexity is even increased with GICMP owing to the parallel computing of R/G phase values in parallel. However, ICMP and GICMP algorithms trade complexity for substantial performance improvement, which makes them much more promising algorithms.

## ► Testbed measurements

To go further in the performance analysis of the proposed algorithms, we took the opportunity of a the PAPRICA project to lead MER measurements on a real testbed hosted by an industrial partner. The goal was to evaluate the impact of the PAPR reduction on the system as a whole. The platform was equipped with a complete DVB-T2 modulator set integrating the GICMP algorithm, a digital predistortion stage and a radio front-end embedding a Class AB or a Doherty amplifier.

Many measurements have been led among which the MER performance evaluation using different power constraints $Γ$={3,5,10} dB. As an example, the MER vs time measurements for the Doherty amplifier have been plotted in Fig. 6.17. The figure exhibits the MER evolution during the transmission of 8 successive DVB-T2 superframes of about 250ms, with some null signal between each superframe. In each case, the total output power and the IBO are fixed for all the tested configurations. As evident from the plots, it is confirmed that the used of the GICMP algorithm leads to a clear improvement of the MER. The long term measurements have been reported in Table 6.4 for both amplifiers. We then conclude that 2 dB improvement can be expected with the algorithm as soon as the power boost exceeds 5 dB.

As PAPR reduction is expected to yield power efficiency improvement of the transmission chain, further tests
## 2. Practical design of PAPR reduction algorithms

<figure><img src="image_29.png" /><figcaption>FIGURE 6.17– MER vs time measurements with Doherty test amplifier at output power 210W.</figcaption></figure>

<table><caption>TABLE 6.5– Average power consumption at a target MER of 36 dB</caption><thead><tr><th></th><th>No PAPR reduction</th><th>GICMP, PC=5dB</th></tr></thead><tbody><tr><td>Power consumption</td><td>313W</td><td>284W</td></tr></tbody></table>

were conducted at the level of the power consumption of the amplifier. More precisely, when PAPR algorithm was activated, we tried to reduce the power supply of the amplifier to modify the power consumption until achieving a target MER at constant output power. As shown in table 6.5, we managed to reduce the consumption of the amplifier of about 10% only constraining the power boost of the reserved tones to 5 dB. This reduction in energy consumption confirms the “green” benefit of the proposed algorithm at a time when all transmitter manufacturers are working at improving the energy efficiency of their systems.

## 2.6 CONCLUSION

Even if PAPR reduction has been a widely studied topic for more than 20 years, no practical implementation of any algorithm have been adopted in commercial products by now. As we worked in some collaborative projects with device manufacturers in the field of TV transmitters, we had the opportunity to better understand the major constraints and issues to address for practical implementation of PAPR reduction algorithms. From the good performance/latency/complexity trade-off shown in the foregoing sections, the proposed ICMP but especially GICMP algorithm, can be considered as a good candidate for future implementations of DVB-T2 and ATSC3.0 green transmitters.

Further works on PAPR reduction and green transmitter design have still to be conducted, especially trying to integrate in a unified model the whole transmission chain characteristics. This is the aim of the subject introduced in the following section.

### Summary (PhD/Dissemination/Projects)

- 1 PhD (R. Mounzer) and 1 Post-Doc (K. Bulusu)

- 1 submitted publication to IEEE Transactions on Broadcasting

- 1 pattent [P.2]

- 4 communications in international conferences and workshops [C.8][C.22][C.24][C.30]

- 1 regional project (PAPRICA) and 1 Eurostar project (GreenTEA)
## 3 THEORETICAL ANALYSIS OF JOINT PAPR REDUCTION AND PREDISTORTION

### 3.1 MOTIVATION

As previously explained, the two main methods usually advocated in literature to mitigate the effects of power amplifier non-linearity are the PAPR reduction and linearization techniques, respectively. Hence, complementary to the PAPR reduction techniques discussed in the previous section, the optimization of the overall performance of a transmitter can be improved by means of linearization techniques which try to compensate for the power amplifier non-linearities.

Two approaches can then be followed for the combination of the PAPR reduction and linearization techniques: non-collaborative approach and joint approach. The non-collaborative approach simply consists in cascading a PAPR reduction module and a linearization one, letting them operate independently. Indeed, the PAPR reduction parameters are optimized and adjusted independently from the linearization and vice versa. However, many studies focusing on the performance results associating PAPR reduction and linearization techniques have highlighted some opposite effects due to mutual interactions between the two functions [SPCK04, KC06, HCVG09, RL03, RHL+04, BAT+11, CY09]. As a result, the non-collaborative approach appears as being simple however sub-optimal. To avoid this, it makes sense to envisage a collaborative or joint treatment guaranteeing the global optimal usage of the power amplifier.

Numerous simulation results exist in the literature concerning these two approaches. Yet, only few contributions have been made on the analytical aspects, for example providing expressions of in-band or out-of-band distortions of the transmitted signals [GOU13, KHNSL12, H+13]. Having a complete and unified analytical model would however be beneficial to predict the overall performance of the system depending on the implemented algorithms for PAPR reduction and linearization. Besides, such a model would allow for a better understanding of the abovementioned mutual effects and provide useful analytical tools towards a global transmitter optimization.

During the TEPN project (Towards Energy Proportional Networks) taking part of the CominLab LabeX framework, we launched a PhD program with the aim of providing new contributions on the analytical level for the performance evaluation of transmitter architectures embedding PAPR reduction and linearization modules.

### 3.2 TRANSMITTER ARCHITECTURE MODEL

Our studies have been based on a generic block diagram of the transmission chain with clipping and predistortion stages preceding the PA, as depicted Fig. 6.18. The multicarrier signal $x_1(t)$ becomes $x_2(t)$ after clipping, and $x_3(t)$ after the predistortion operation. The output of the PA is $z(t)$. Such a model can then be particularized specifying the effectively used algorithms or components as detailed hereafter. From such an architecture, the idea will be then to derive the analytical expressions for some commonly used figures of merit revealing the level of signal distortions at the output of the power amplifier, e.g. EVM (Error Vector Magnitude) or ACPR (Adjacent Channels Power Ratio).

#### ▶ PAPR effects modeling

Thanks to the central limit theorem, it is well accepted that OFDM signals with a large number of subcarriers can be approximated by a complex Gaussian random process with zero mean [BLG02]. However, after PAPR reduction, the distribution of the signal may change, or at least its parameters. Although numerous PAPR algorithms are available in the literature, there have been very few studies at the level of the theoretical modeling of such algorithms to understand their effect on the signal statistics modification before and after PAPR reduction. The only contributions concern the probabilistic PAPR reduction methods [BFH96, MH97, BP08] which are however not downward compatible. As far as tone reservation methods are concerned, the distribution of the signal after PAPR reduction is likely to be different for each method depending on the additive signal $c(t)$. Therefore, it is not straightforward to provide a unified framework on this aspect. Such a question is indeed part of the research topics I propose to address as perspectives in Chap. 9. However, in the work done these
## 3. Theoretical Analysis of Joint PAPR Reduction and Predistortion

<figure><img src="image_30.png" /><figcaption>FIGURE 6.18– Generic block diagram model of a transmitter equipped with PAPR and predistortion functions.</figcaption></figure>

<figure><img src="image_31.png" /><figcaption>FIGURE 6.19– Probability density function of the signal amplitude before and after Clipping.</figcaption></figure>

last years, we have focused our attention on the clipping technique due to its popularity and its straightforward reduction gain. It is then rather simple to predict the probability density function (PDF) of the amplitude of the output signal.

Let us consider the clipping function using the following relationship between the input and the clipped signal

$$x_2(t) = \begin{cases} x_1(t) & \text{if } |x_1(t)| \le A_{max} \\ A_{max} e^{j\phi(x)} & \text{if } |x_1(t)| > A_{max}. \end{cases} \qquad (6.31)$$

with $A_{max}$ the amplitude of the clipping threshold. The amplitude PDF $f_{x_2}$ of the clipped signal can then be simply written as

$$f_{x_2}(r) = \begin{cases} \frac{2r}{P_{x_1}} e^{-\frac{r^2}{P_{x_1}}} & \text{if } r < A_{max} \\ e^{-\Lambda} & \text{if } r = A_{max} \end{cases} \qquad (6.32)$$

where $r$ is the magnitude of the signal, $P_{x_1}$ the average power of the input signal $x_1(t)$ and $\Lambda$ is defined as the clipping power ratio, i.e. $\Lambda = \frac{A_{max}^2}{P_{x_1}}$. The second line ($r = A_{max}$) is simply obtained integrating the Rayleigh PDF from $A_{max}$ to $r \to \infty$. Fig. 6.19 presents the amplitude distribution of the input signal $x_1(t)$, and the clipped signal $x_2(t)$. In our study, we have thus assumed that PAPR reduction could be modeled as obtaining a signal $x_2(t)$ which amplitude follows the PDF given by (6.32) controlled by a single parameter $\Lambda$.

### ► Power Amplifier Models

One central aspect of the proposed work is to integrate accurate models for the power amplifier since it is the key element which brings distortions on the signal. Conventional static power amplifier models, such as AM/AM and AM/PM characteristics, can represent, with reasonable accuracy, the power amplifier behavior driven by narrowband input signals. However, in practice the actual amplitude and phase of the high PA output voltage are not only determined by the current input voltage. In reality, the output of high power amplifiers such as those used in wireless base stations depend on the instantaneous inputs, but also on the previous inputs too. This kind of phenomenon is described as memory effects and it is illustrated in Fig. 6.21. Besides, wideband signals also tend to induce memory effects in the PA. In such cases, memoryless models can be ineffective. Thus, accurate representation of the memory effects is crucial as further detailed in [VRM01].

During the past few decades, various models have been proposed trying to reflect with more or less accuracy the true behaviour of power amplifiers. A broad view on the subject can be given by distinguishing three types of models : memoryless and quasi-memoryless models, and models with memory. As already introduced in section 2.5, the most popular but simple model were proposed by Rapp [Rap91] for amplifiers based on semiconductors (SSPA). This Rapp model is memoryless, i.e. its output at a determined time instant does not depend on the previous entries. In addition, it does not present any phase distortions. The AM/AM transfer curve of the PA is then given by

$$H_{PA}(r) = \frac{r}{\left(1 + \left(\frac{r}{A}\right)^{2b}\right)^{\frac{1}{2b}}}, \qquad (6.33)$$
<figure><img src="image_32.png" /><figcaption>FIGURE 6.20– AM/AM power amplifier characteristics following the Rapp Model</figcaption></figure>

<figure><img src="image_33.png" /><figcaption>FIGURE 6.21– Example of AM/AM power amplifier characteristics with memory effects</figcaption></figure>

where *r* is the magnitude of the input voltage, *A* is the amplitude of the saturation output voltage of the amplifier and *b* is the 'knee factor' parameter which controls the smoothness of the transition between the linear and the saturation zones of the characteristics. Fig. 6.20 presents the AM/AM characteristic of the Rapp model for different knee factor values with a unitary amplification gain. It has to be noted that as the value of *b* increases, the Rapp model approaches to a soft envelope limiter model.

Another popular and useful PA model is the memoryless polynomial model which principle relies on a parametric Taylor series expansion of the true AM/AM characteristics of a given PA [JBS00]. The PA output is then expressed in baseband by the following odd order polynomial :

$$H_{PA}(r) = \sum_{l=0}^{L_p} b_{2l+1} r^{2l+1} \qquad (6.34)$$

where $L_p$ denotes the nonlinear model order and $b_{2l-1}$ are the polynomial coefficients<fnref n="8" />. Making the coefficients complex will result in a quasi memoryless polynomial model. Other models have been proposed for various amplifiers technologies as for instance the Saleh model [Sal81] for memoryless Traveling Wave Tube Amplifiers.

Finally, in the category of memory amplifier models, the most accurate model is the one based on Volterra series. A Volterra series in a combination of linear convolution and a nonlinear power series so that it can be used to describe any nonlinear stable system with fading memory. The Volterra series model can achieve higher accuracy than other memory models at the cost of very high computational complexity. More practical models have thus been proposed [BF82, GMB05, NG66], which can essentially be viewed as simplified special cases of the Volterra model. In our study, we chose to use the very popular memory polynomial model [KK01] which is also a truncation of the general Volterra series, by only keeping the diagonal terms in the Volterra kernels. Thus, the number of parameters is significantly reduced compared to conventional Volterra model, and the computational complexity of the coefficients identification is remarkably decreased. The memory polynomial model can be viewed as parallel connected memoryless nonlinear models, each with individually delayed input signal so that the outputs of the nonlinear sub-models would be summed up.

Hence, the relationship between the input and output of the memory polynomial model is given by the following equation

$$z(t) = \sum_{q=0}^{Q} \sum_{l=1}^{L} b_{lq} x(t - q\tau) |x(t - q\tau)|^{2(l-1)}, \qquad (6.35)$$

where *Q* is the memory depth, *τ* is a delay parameter, *L* is the polynomial order and $b_{lq}$ are complex coefficients. All these parameters reflect the nonlinearities and memory effects of the PA and can be obtained through measurements and estimation algorithms for a particular amplifier [MMK+06].

## Linearization model

<footnote n="8">8. Note that the odd order comes from the bandpass assumption of power amplifier transfert function.</footnote>