Reference number : GC-2017-Q2-00535, amendment number : , agreement type : G, recipient legal name : Yu, Wei (University of Toronto), 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 : This research project focuses on novel optimization technique for ultra-dense networks. We consider a dense deployment of cellular access-points and/or device-to-device links, where multiple transmit and receive pairs mutually interfere with each other, and propose a novel method for spectrum sharing based on an optimization technique called fractional programming. The proposed method is capable of efficiently finding locally optimal solutions to the coordinated scheduling, beamforming, and power control problem across the entire network. Numerically, the fractional programming solution is iterative in nature, but each iteration step typically involves a closed-form solution and is therefore easy to implement. Optimized coordinated transmission is the key to ensuring spectrally compatible bandwidth sharing in ultra-dense networks. As a concrete application, the proposed research will investigate fractional programming based coordinated scheduling scheme for cellular networks with flexible duplex capability, where simultaneous transmissions in uplink and downlink can significantly improve area spectral efficiency. The proposed research will also apply the fractional programming technique to the optimization of spatial multiplex and nulling in large-scale multiple-antenna systems. The proposed method can also be applied to the optimal scheduling of relay links for interference cancellation in cellular networks. Finally, the proposed research will investigate signaling and channel state acquisition strategies to allow distributed implementation of fractional programming techniques. The wireless industry is undergoing profound transformation in the upcoming Big Data era. The introduction of network intelligence in optimizing and adapting network operations dynamically and in real-time will be a key technological step in meeting the increasing demands in important application areas such as smart home, smart office, smart city, and self-driving cars._x000D_
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_x000D_, program purpose french : This research project focuses on novel optimization technique for ultra-dense networks. We consider a dense deployment of cellular access-points and/or device-to-device links, where multiple transmit and receive pairs mutually interfere with each other, and propose a novel method for spectrum sharing based on an optimization technique called fractional programming. The proposed method is capable of efficiently finding locally optimal solutions to the coordinated scheduling, beamforming, and power control problem across the entire network. Numerically, the fractional programming solution is iterative in nature, but each iteration step typically involves a closed-form solution and is therefore easy to implement. Optimized coordinated transmission is the key to ensuring spectrally compatible bandwidth sharing in ultra-dense networks. As a concrete application, the proposed research will investigate fractional programming based coordinated scheduling scheme for cellular networks with flexible duplex capability, where simultaneous transmissions in uplink and downlink can significantly improve area spectral efficiency. The proposed research will also apply the fractional programming technique to the optimization of spatial multiplex and nulling in large-scale multiple-antenna systems. The proposed method can also be applied to the optimal scheduling of relay links for interference cancellation in cellular networks. Finally, the proposed research will investigate signaling and channel state acquisition strategies to allow distributed implementation of fractional programming techniques. The wireless industry is undergoing profound transformation in the upcoming Big Data era. The introduction of network intelligence in optimizing and adapting network operations dynamically and in real-time will be a key technological step in meeting the increasing demands in important application areas such as smart home, smart office, smart city, and self-driving cars._x000D_
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_x000D_, agreement title english : Optimized spectrum sharing of ultra-dense networks, agreement title french : Optimized spectrum sharing of ultra-dense networks, agreement number : CRDPJ, agreement value : 187040.0, 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 2021-2022)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2021-2022)., 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