bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence Mapping
Authors: Wakefield Jon 
Published: May 2020

Abstract

As data availability escalates, there has been a corresponding increase in the production of maps displaying the prevalence of a large range of health and demographic outcomes – an endeavor that has been labeled
prevalence mapping
. In this article, we distinguish between modeling at the areal level, that is
small area estimation
(SAE), and at the point level, which is referred to as
model‐based geostatistics
(MBG). Often, maps are produced for low‐ and middle‐income countries based on household surveys which have complex designs. Bayesian smoothing models are convenient for both SAE and MBG, and computation is no longer a major problem for most prevalence mapping endeavors. To illustrate the two approaches, we form estimates of measles vaccination rates for Nigeria, using data from the 2013 Demographic Health Survey (DHS). While prevalence maps are clearly of use in many contexts, we encourage care in their production and advocate respecting the survey design in analysis, and summarization at a granularity which is both meaningful and sufficiently precise so as to avoid being misleading. Prevalence mapping remains in its infancy, and research is required in a number of key areas, in particular to appropriately characterize uncertainty and validate models.
Statistics and Terrorism: Insights into Lethality of Terrorism Through Bayesian Modeling
Authors: Python Andre , Brandsch Jürgen , Illian Janine B. , Jones‐Todd Charlotte M. , Blangiardo Marta 
Published: May 2020

Abstract
The increasingly growing availability of large disaggregated datasets on terrorism along with advances made in the fields of statistics and data science has allowed scholars to better understand the patterns of non‐state terrorism at fine spatial and temporal scales. While acknowledging important limitations that stem from the analysis of data on terrorism, we present a Bayesian hierarchical modeling approach that contributes to explaining fine‐scale patterns of the lethality of worldwide non‐state terrorism.
Variograms for Functional Data
Authors: Elayouty Amira 
Published: May 2020

Abstract
In several applications, data are collected as functions observed at a set of locations of a region, inducing spatially correlated functional data. The analysis of such data is performed by adapting and extending the spatial statistical tools for functional data. The variogram is a very popular measure for describing the spatial covariance structure of a spatial process. This article focuses on the extension of variograms for functional data and provides a review for the computation and estimation of different types of functional variograms.
Pilot‐Assisted Channel Estimation
Authors: Jiménez Juan C. Estrada , García M. Julia Fernández‐Getino , Méndez‐Romero Diego 
Published: May 2020

AbstractChannel estimation is a challenging task in coherent wireless communications systems since it highly impacts data detection performance. To acquire channel state information, known pilot symbols are commonly inserted in the signal to be transmitted. Then, at the receiver, the channel is estimated comparing the received signal with the pilot symbols. Pilot symbol assisted modulation (PSAM) is a channel estimation technique commonly used, where known symbols are transmitted over dedicated resources and they are used as reference signals. PSAM spends valuable bandwidth to transmit the pilot signal in order to obtain low channel estimation error. Currently, 5G technologies have been using different versions of PSAM to estimate the channel and different patterns have been tested to improve the communication performance.
Modulations with Low Peak‐to‐Average Power Ratio
Authors: Banelli Paolo , Baruffa Giuseppe , Buzzi Stefano , Colavolpe Giulio , Foggi Tommaso , Rugini Luca , Ugolini Alessandro 
Published: May 2020

AbstractWe compare the main multicarrier modulation formats when employed over channels with nonlinear amplification. Using a general and unified discrete‐time model that encompasses orthogonal frequency division multiplexing (OFDM) and its most popular alternatives, we perform a comparison using the achievable spectral efficiency, computed in the presence of specific channel and amplifier models, as performance indicator. This provides a more precise quantitative measure of the effect that the different peak‐to‐average power ratio (PAPR) of these modulations has on the ultimate performance. In the numerical results, different LTE channel models are considered. We show that, depending on the considered channel, the winning modulation format is not always the same. In any case, modulation formats other than OFDM exhibit the best performance.
Polar Codes
Authors: Bioglio Valerio 
Published: May 2020

Abstract
Polar codes have been recently adopted as control channel coding scheme for upcoming 5G NR framework. Their mathematical foundations lay on the polarization effect, whose discovery in late 2000s represented a real breakthrough for the information theory community. In order to be included in an industrial standard, polar codes went through a refinement process that permitted 3GPP to improve their error correcting performance while keeping a limited decoding latency. The results of these efforts is a synthesis of all known advancements in the field and truly represents the state‐of‐the‐art of polar coding knowledge today.
Random Access for Cellular Systems
Authors: Mahmood Nurul H. , López Onel A. , Clazzer Federico , Munari Andrea 
Published: May 2020

AbstractWireless connectivity has become a ubiquitous part of our everyday life. Owing to its very nature, the wireless channel is a shared medium, where simultaneous transmissions from neighboring transceivers operating in the same frequency can interfere with each other. Access to the shared wireless medium needs then to be strictly regulated to ensure efficient utilization of the scarce spectral resources. The admission control process to handle the access of multiple coexisting transmitters over the same wireless channel is typically initiated relying on random access‐related policies, having users send information (control or data packets) in an uncoordinated fashion. The design goal for random access techniques differs in different systems, mainly depending on the catered service. The current fourth‐generation long‐term evolution system is primarily designed to serve cellular broadband users, and hence its random access procedures have been designed to support contention from a limited number of users, with the aim to negotiate and exclusively allocate channel resources to them. Conversely, emerging fifth‐generation new radio is designed to allow the coexistence of multiservice communication. Similarly, systems that are exclusively designed to support machine‐type communication targeting Internet of Things applications, such as SigFox, LoRA, and NB‐IoT, have designed their random access mechanism to serve a large number of low power, low‐cost devices with small payload and intermittent transmissions. On the other hand, indoor wireless local area networks like Wi‐Fi are designed for a decentralized access of several users. Finally, random access techniques like nonorthogonal multiple access and grant‐free transmissions have emerged to support machine‐type communication encompassing both its massive and critical aspects, in line with the increasing importance of such critical services in emerging systems.
Multiuser Scheduling
Authors: de la Fuente Alejandro 
Published: May 2020

Abstract
Scheduling and resource allocation (SRA) strategies play a crucial role in the emerging fifth‐generation (5G) systems based on massive multiple‐input multiple‐output (MaMIMO) transmissions. The set of resources to allocate is increased, adding to the time, frequency, modulation, and coding resources, the spatial dimension introduced by MaMIMO. These spatial resources are provided by precoding schemes based on the channel state information knowledge at the transmitter side (CSIT). The joint optimization of all the input variables together with the quality of service (QoS) requirements established by the upper layers results in a complex cross‐layer optimization problem. Different metric criteria for SRA algorithms are studied in the literature. MaMIMO SRA is based on CSIT knowledge to select a feasible set of users to allocate the resources of a scheduling interval. This article provides a detailed view of the required mechanisms to understand the SRA process in the emerging 5G systems. To conclude this article, some challenging solutions regarding the utilization of heterogeneous scenarios, MaMIMO transmissions, millimeter wave (mmWave) frequencies, and artificial intelligence are presented.
High‐Density Channels
Authors: Cai Xuesong , Zhang Chao , Fan Wei 
Published: May 2020

AbstractIn the future, fifth‐generation communications system (5G) is expected to provide reasonable mobile broadband experience to high‐density users in stadium, gym, shopping mall, etc. As the fundamental limitation is attributed to the propagation environments, it is essential to understand profoundly the high‐density channels, say, the propagation channel in the environments where the user density could be very high. In this article, seven different environments are considered. The targeted environments include stadium (or gymnasium), shopping mall, airport, hall, street canyon, indoor (or indoor office), and crowded area. The propagation investigations in the literature for the seven environments are reviewed in terms of channel sounding, parameter estimation, channel characterization and modeling, etc. The review of the high‐density channel facilitates the “great service in a crowd” defined in 5G.
Indoor Office Channels
Authors: Kürner Thomas 
Published: May 2020

AbstractIndoor Ultra‐high Broadband Access with high traffic densities inside office buildings brings the indoor office channel into the focus. Whereas in the past decade the indoor office channel in the UHF range was subject to intense channel modeling and channel characterization approaches, with the advent of 5G mmWave channels are raising attention. After introducing the key characteristics and main differences of propagation in the UHF and mmWave frequency range, respectively, the first part of the article indoor office channels describes empirical, semiempirical, and deterministic path loss models for both the UHF and the mmWave frequency range. A detailed description is provided for the semiempirical Motley–Keenan model and its various extensions. These models allow a narrowband channel characterization and provide the large‐scale characteristics. These models are relevant for the planning and optimization of radio access points as well as an enabler for system‐level simulations. The second part introduces channel models capable of providing temporal and spatial channel characteristics. This includes approaches to derive models for double‐directional channels, which are required to simulate and investigate multi‐antenna systems and beam‐forming algorithms especially in the mmWave range. Furthermore, an approach to describe the impact of human blockage is provided. As exemplary approaches, the extended Saleh–Valenzuela model and the TGad channel model are described.
MassiveMIMOChannels
Authors: Gunnarsson Sara , Van der Perre Liesbet , Tufvesson Fredrik 
Published: May 2020

AbstractMassive MIMO (multiple‐input multiple‐output) is a fundamental technology in 5G systems. The characteristics of the radio channel experienced when operating with large antenna arrays differ from those of conventional multiple antenna systems. Hence, it is important to specifically characterize and model the underlying propagation channels with large antenna systems in mind. The channel models need to be realistic and accurate, but of low complexity, in order to be used to develop and assess the performance of future systems in a good way. This article gives an overview of state‐of‐the‐art of massive MIMO channels and related models. First, some fundamentals of massive MIMO propagation, including a comparison between micro‐wave and mm‐wave massive MIMO as well as the influence of user terminals, are provided. Then, channel characteristics that have been shown in measurements to be important in massive MIMO channels are presented. These include spherical wavefronts, nonstationarity, 3D propagation, and polarization effects. Further on, some channel‐dependent characteristics, which are experienced in massive MIMO systems, are in focus. In this article, we outline user separability and channel hardening, as an effect of favorable propagation conditions. Different channel modeling approaches are discussed, including the independent and identically distributed (i.i.d.) complex Gaussian channel model, correlation‐based channel models like the Kronecker and Weichselberger channel models, geometry‐based reference models, geometry‐based stochastic channel models (GSCMs), ray‐tracing and map‐based approaches. A brief overview of recently developed channel models, targeting massive MIMO channels, is also provided. Lastly, we discuss opportunities and challenges related to massive MIMO channels and modeling.
3D MIMOChannels
Authors: Zhang Ruonan , Jiang Yi , Zhai Daosen 
Published: May 2020

AbstractThe fifth‐generation (5G) mobile communication systems require high spectrum efficiency due to the explosive increase of data traffic and green networking requirement. The demand for higher spectrum and energy efficiency has driven system designers to exploit more spatial degrees of both the elevation and azimuth domains through the use of large‐scale antenna systems with two or three‐dimensional (3D) array structures. The performance of full‐dimensional multiple‐input‐multiple‐output (FD‐MIMO) depends critically on both the space–time transmission schemes and 3D channel propagation characteristics. Therefore, it is important to understand and describe the 3D spatial propagation of signals in multipath radio channels. This article aims to provide a comprehensive introduction to the fundamental concept and approaches characterizing and modeling the 3D spatial channels. We first present the bi‐directional space‐time scattering models of multipath channels and the polarized multipath components (MPCs). We then briefly introduce the development of 3D channel modeling and the main projects and standards in the industrial community. Finally, we summarize and discuss the current 3D channel models based on extensive field measurement for various cellular network scenarios, such as outdoor, indoor, outdoor‐to‐indoor (O2I), and vehicular communication scenarios.
MassiveMIMOAntenna Designs
Authors: Gao Yue , Su Wei , Zhang Xiuyin , Cao Yunfei 
Published: May 2020

AbstractMassive multiple‐input multiple‐output (MIMO) has attracted significant interests in both academia and industry with recent development of signal processing and information theory. It has been considered as one of the most promising technologies for 5G communication systems. The large‐scale antenna array for base stations naturally becomes the key to deploy the Massive MIMO technologies in addition to baseband signal processing. In this article, we shall start from the characteristics of conventional MIMO antennas to the areas of Massive arrays. Several notable previous works have been presented in this article as examples to show the idea.
5GWireless Testbeds
Authors: Zhang Peize , Yi Cheng , Wang Haiming 
Published: May 2020

AbstractFifth‐generation (5G) mobile communication systems are being rolled out in the real world, bringing higher frequencies, more complicated transmission schemes, and denser networks. To ensure the successful operation of 5G, the evaluation of the performance of several promising technologies requires rigorous field trialing and validation. To that end, the 5G wireless testbed design based on reconfigurable hardware and open‐source software is discussed in detail from the perspectives of the physical layer and higher levels. Meanwhile, there are some new considerations regarding the actual system placement, such as the mechanical design and network architectures. Based on these observations, the state‐of‐the‐art 5G testbeds operating at sub‐6 GHz and the millimeter‐wave band are reviewed, with a focus on multiuser massive MIMO systems.
Small Cell Network Modeling and Analysis
Authors: Yang Howard H. , Quek Tony Q.S. 
Published: May 2020

AbstractSmall cell networks are deemed one of the key solutions for next‐generation (5G) wireless networks. In such networks, along with the spatial densification of access points, temporal traffic can also vary largely from cell to cell. To this end, a complete understanding of the impact from spatial and temporal aspects is thus essential for network operators to adequately advance the deployment of small cell networks. In this article, based on stochastic geometry and queuing theory, we develop a mathematical framework that captures the interplay between the spatial location of small access points (SAPs), which determines the magnitude of mutual interference, and their temporal traffic dynamic. We derive a tractable expression for the signal‐to‐interference‐plus‐noise ratio (SINR) distribution, as well as the mean delay distributions under two different scheduling policies, i.e. the random scheduling and round robin. We also verify the accuracy of our mathematical analysis via simulations. Based on our analysis, we find a number of useful guidelines for the deployment of small cell networks.
Radio Resource Management in Small Cell Networks
Authors: Wang Li‐Chun , Chao Yung‐Sheng 
Published: May 2020

AbstractUltra‐dense small cell (UDSC) network will play a key role to cope with the capacity issue for 5G cellular mobile systems and beyond because future broadband mobile applications require high‐speed transmission and low latency. Nevertheless, deploying small cell deployment will need to face the challenges of severe interference and excessive energy consumption in very dynamic environments. To address these issues, in this article we introduce a data‐driven resource management (DDRM) framework combined with power control, channel rearrangement, and dynamic antenna clustering (DAC). In particular, an unsupervised learning affinity propagation clustering is applied to UDSC to identify cluster heads, i.e. the cell causing most serious interference to its neighboring cochannel cells. Then, these cluster heads will lower its transmission power. We call this learning‐based interference management approach as affinity propagation power control (APPC). We show that DDRM with APPC can improve energy efficiency and reduce interference for UDSC, while taking account of cell switching on/off, transmission power adjustment, and traffic loads simultaneously.
Energy‐AwareD2DCommunications
Authors: Feng Daquan , Huang Xiaoli , Long Litai , Qian Gongbin , Tang Jianhua , Cao Yue 
Published: May 2020

AbstractDevice‐to‐device (D2D) communications, which enable proximity users to communicate directly without passing through BS, have been considered as one of the key techniques in the future 5G networks. By taking advantage of the physical proximity, D2D communications can significantly enhance the quality of experience (QoE) of users and increase resource utilization. Meanwhile, due to the ever‐increasing power consumption of information and communication technology (ICT) industry and the slow progress in battery technology of the smart devices, energy efficiency has been considered as a key performance indicator for the 5G networks. Thus, energy‐efficient D2D communications design has attracted considerable attention from both the industrial and academic communities. There have been plenty of discussions on this issue, for instance, (i) energy‐efficient D2D transmission technologies including efficient power control, mode selection, cross‐layer optimization, and energy harvesting; (ii) novel D2D‐based energy‐saving network deployment including D2D relay cooperative communications and D2D‐aided heterogeneous networks; and (iii) D2D multiple‐input and multiple‐output (MIMO) transmission. In this article, we provide an extensive overview of these technologies and present the state of the art of each aspect. In addition, we summarize the main findings of the discussed techniques and also identify some open research problems.
Edge/Fog Computing Networks
Authors: Chen Zhi , Li Lingxiang , Siew Marie , Quek Tony Q.S. 
Published: May 2020

AbstractAs a main driver of 5G, the future mobile network is going to create a hyper‐connected Internet of Everything (IoE) world which requires the network to be scalable, versatile, and energy smart. The convergence of communication and computing is a promising solution of IoE while the introduction of fog/edge computing makes this possible in the future mobile networks. This article provides a comprehensive survey of the fog/edge‐computing‐enabled mobile network. Specifically, the motivation of introducing fog/edge computing, the standardization of fog/edge computing in 5G, and the mobile communication network architecture with fog/edge computing are reviewed. The challenges such as the scalability and extreme heterogeneity of resource management in IoE, and the advantages of using fog/edge‐based architecture, are also discussed. Under the fog/edge‐computing‐driven mobile communication network architecture, a distributed resource allocation mechanism based on economics is presented. The economics models and analysis study the underlying, and possibly conflicting objectives and incentives of various stakeholders, with pricing solutions providing a way for the optimization of objectives like social welfare, profit, or fairness. As such, it can be a potential powerful tool in solving the aforementioned challenges. While pricing for resource allocation has a vast existing literature, the analysis and schemes cannot be implemented directly due to the unique characteristics of 5G cloud‐fog/edge networks, hence providing a vast scope for potential research. In light of this, we finally outline some unique characteristics to consider when applying economics to aid resource allocation in 5G cloud‐fog/edge networks.
Business Models of Network Slicing
Authors: Kukliński Sławomir , Tomaszewski Lechosław 
Published: May 2020

AbstractThe development of network softwarization technologies, which leads to network slicing concept, will cause the significant disruption of the current telecommunications sector. Its significance is still underestimated. New roles are expected to appear in the ecosystem, and the mutual relations will be established dynamically. In this article, we have made an attempt to show how network slicing can impact business models of telecommunication network operators. The traditional models of fixed/mobile operators have been described. For reference, the cloud delivery models have been shown. Then the approaches of telecom industry alliances and standard developing organizations are presented, which are conservative and simple evolution of the existing business models. Finally, the comprehensive future business model of network slicing is presented, which is based on widely accepted network slicing concepts. In the concept, the software dimension of network slicing has been emphasized, especially the significant role of brokers that can provide infrastructure brokering, service brokering, or even slice template brokering. The implementation of the proposed approach requires some changes in the Management and Orchestration (MANO) framework to unleash the full technoeconomical potential of network slicing.