Reference number : GC-2017-Q2-00419, amendment number : , agreement type : G, recipient legal name : Damen, Mohamed Oussama (University of Waterloo), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Collaborative Research and Development Grants - Project, program name french : Subventions de recherche et développement coopérative - projet, program purpose english : Massive multiple-input multiple-output (MIMO) systems, or large scale MIMO, are multiuser multiple antenna technologies that constitute one of the front runners proposed in the recent literature for solving the impending wireless network crunch that will result from the ever increasing number of subscribers and their data-hungry applications envisioned for the Internet of Things and 5G systems. In this proposal, we will tackle the problem of designing low complexity signal processing algorithms at both ends of large-scale MIMO transmission and reception.  We will use our experience in designing efficient decoding algorithms for MIMO systems at a small-to-medium scale and exploit the nature of the massive MIMO in order to propose novel techniques taking advantages of the new channel characteristics, i.e., channel matrix sparsity and channel hardening around its mean value, while maintaining efficient signal processing algorithms. The system complexity will be distributed between the base stations, which can afford more complex algorithms, and the end-user terminals with low complexity processing constraints. At the base stations, we will consider the design of hybrid analog and digital beamforming algorithms with limited feedback on channel state information in order to decrease the number of costly radio frequency chains and improve the system efficiency. Then, we will consider the design of multiuser scheduling algorithms that take advantage of the sparse channel matrix for efficiently reducing it by blocks of manageable sizes. The design of training sequences required for beamforming  and scheduling will also be investigated and analyzed in depth. Finally, we will tackle the problem of designing distributed massive MIMO systems, with practical considerations such as real-time processing, estimation errors, synchronization and interference management. Research and development on efficient transceivers designs targeting next generation wireless communications standards will have important commercial benefits to the Canadian IT sector, and this proposal will lead to the formation of two HQP who will gain both theoretical and practical skills in one of the most important and fast growing sectors of the Canadian economy._x000D_
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_x000D_, program purpose french : Massive multiple-input multiple-output (MIMO) systems, or large scale MIMO, are multiuser multiple antenna technologies that constitute one of the front runners proposed in the recent literature for solving the impending wireless network crunch that will result from the ever increasing number of subscribers and their data-hungry applications envisioned for the Internet of Things and 5G systems. In this proposal, we will tackle the problem of designing low complexity signal processing algorithms at both ends of large-scale MIMO transmission and reception.  We will use our experience in designing efficient decoding algorithms for MIMO systems at a small-to-medium scale and exploit the nature of the massive MIMO in order to propose novel techniques taking advantages of the new channel characteristics, i.e., channel matrix sparsity and channel hardening around its mean value, while maintaining efficient signal processing algorithms. The system complexity will be distributed between the base stations, which can afford more complex algorithms, and the end-user terminals with low complexity processing constraints. At the base stations, we will consider the design of hybrid analog and digital beamforming algorithms with limited feedback on channel state information in order to decrease the number of costly radio frequency chains and improve the system efficiency. Then, we will consider the design of multiuser scheduling algorithms that take advantage of the sparse channel matrix for efficiently reducing it by blocks of manageable sizes. The design of training sequences required for beamforming  and scheduling will also be investigated and analyzed in depth. Finally, we will tackle the problem of designing distributed massive MIMO systems, with practical considerations such as real-time processing, estimation errors, synchronization and interference management. Research and development on efficient transceivers designs targeting next generation wireless communications standards will have important commercial benefits to the Canadian IT sector, and this proposal will lead to the formation of two HQP who will gain both theoretical and practical skills in one of the most important and fast growing sectors of the Canadian economy._x000D_
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_x000D_, agreement title english : Low complexity large scale MIMO processing, agreement title french : Low complexity large scale MIMO processing, agreement number : CRDPJ, agreement value : 89356.0, agreement start date : 2017-08-23, 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 2019-2020)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2019-2020)., 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