Reference number : GC-2017-Q1-01433, amendment number : , agreement type : G, recipient legal name : Champagne, Benoit (McGill University)|Champagne, Benoit (Université McGill), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : DND/NSERC Discovery Grant Supplement, program name french : Supplément aux subventions à la découverte MDN-CRSNG, program purpose english : Extraordinary advances in wireless network technology during the past decade have revolutionized the way in which we use personal communications. As a result of such benefits, the user demand for throughput continues to grow at a stunning rate of 50% annually. Anticipating that current 4th generation (4G) of wireless systems will not meet the demand for future services, standardization bodies have set forth impressive target specifications for the 5th generation (5G), with multi-fold enhancements in data rate, connectivity, energy efficiency, and quality of service (QoS). Reaching such high-end performance in a spectrum congested environment calls for the introduction of new physical layer technologies along with sophisticated signal processing algorithms.
 
 
The long-term goal of the proposed research is to develop and investigate new signal processing concepts, theories and algorithms, to meet the demands of emerging 5G mobile networks and beyond. Key innovative aspects include a focus on location-aware information processing, which provides the unifying theme for the proposed work, along with an emphasis on the use of multi-antenna systems operated in higher frequency bands, i.e. shift towards mm-waves. Within this exacting framework, the short-term objectives of the program are articulated around three complementary topics, namely: (1) modulation formats and waveform design; (2) space-time processing for large-scale antenna arrays; and (3) device localization in ultra-dense networks. Under the first topic, we will study new adaptive multi-carrier modulation (MCM) techniques that take advantage of location-based information to optimize spectrum efficiency over time, across the network. These new schemes will then be extended for application to massive multiple-input multiple-output (MIMO) transceiver configurations. Under the second topic, we will develop improved algorithms for the estimation of location-based parameters, including: direction of arrival (DoA) and time of arrival (ToA). We will also investigate new low-complexity 3D beamforming algorithms, with a focus on beamspace methods. Under the third topic, we will research novel on-line algorithms for the localization and tracking of mobile devices using both line-of-sight (LoS) and non-LOS (NLoS) measurements. Finally, these algorithms will be generalized to distributed forms of processing, for practical application in dense heterogeneous networks.
 
 
This program of research will provide numerous opportunities for HQP training at the M.Eng. and Ph.D. levels, while the main findings will be presented at international conferences and published in highly selective journals., program purpose french : Extraordinary advances in wireless network technology during the past decade have revolutionized the way in which we use personal communications. As a result of such benefits, the user demand for throughput continues to grow at a stunning rate of 50% annually. Anticipating that current 4th generation (4G) of wireless systems will not meet the demand for future services, standardization bodies have set forth impressive target specifications for the 5th generation (5G), with multi-fold enhancements in data rate, connectivity, energy efficiency, and quality of service (QoS). Reaching such high-end performance in a spectrum congested environment calls for the introduction of new physical layer technologies along with sophisticated signal processing algorithms.
 
 
The long-term goal of the proposed research is to develop and investigate new signal processing concepts, theories and algorithms, to meet the demands of emerging 5G mobile networks and beyond. Key innovative aspects include a focus on location-aware information processing, which provides the unifying theme for the proposed work, along with an emphasis on the use of multi-antenna systems operated in higher frequency bands, i.e. shift towards mm-waves. Within this exacting framework, the short-term objectives of the program are articulated around three complementary topics, namely: (1) modulation formats and waveform design; (2) space-time processing for large-scale antenna arrays; and (3) device localization in ultra-dense networks. Under the first topic, we will study new adaptive multi-carrier modulation (MCM) techniques that take advantage of location-based information to optimize spectrum efficiency over time, across the network. These new schemes will then be extended for application to massive multiple-input multiple-output (MIMO) transceiver configurations. Under the second topic, we will develop improved algorithms for the estimation of location-based parameters, including: direction of arrival (DoA) and time of arrival (ToA). We will also investigate new low-complexity 3D beamforming algorithms, with a focus on beamspace methods. Under the third topic, we will research novel on-line algorithms for the localization and tracking of mobile devices using both line-of-sight (LoS) and non-LOS (NLoS) measurements. Finally, these algorithms will be generalized to distributed forms of processing, for practical application in dense heterogeneous networks.
 
 
This program of research will provide numerous opportunities for HQP training at the M.Eng. and Ph.D. levels, while the main findings will be presented at international conferences and published in highly selective journals., agreement title english : Signal Prosessing Techniques for 5G Wireless and mm-Wave Communications, agreement title french : Signal Prosessing Techniques for 5G Wireless and mm-Wave Communications, agreement number : DGDND, agreement value : 120000.0, agreement start date : 2017-06-14, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2020-2021), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2020-2021), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada