Reference number : GC-2017-Q1-00483, amendment number : , agreement type : G, recipient legal name : Hossain, Ekram (University of Manitoba)|Hossain, Ekram (Université du Manitoba), recipient country : CA, recipient province : nan, recipient city : Manitoba, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : The demand for two-way radio communication has increased dramatically and this growth trend is expected to_x000D_
continue. Our industry partner for this project, Tridon Communications, operates a two-way radio_x000D_
communications network and currently it faces the challenge of optimizing the number of radio channels at the_x000D_
different sites in order to maximize the satisfaction of its customers while efficiently utilizing the given total_x000D_
number of radio channels. Also, it lacks a solid methodology to make decisions on network dimensioning and_x000D_
extending the network infrastructure in a cost-effective manner. The proposal is to develop a learning-based_x000D_
method for traffic estimation and admission control for Tridon's two-way radio communication system. This_x000D_
method, which will be delivered to Tridon as a set of algorithms and/or software modules, will be used by_x000D_
Tridon to optimize its network performance by efficiently utilizing the radio channels and controlling_x000D_
admission of the users into the network while satisfying their communication performance requirements. Also,_x000D_
the method will be used for network dimensioning and expansion of the currently deployed system. The project_x000D_
will benefit this Canadian Company to offer two-way radio communication services in a competitive price with_x000D_
customers' satisfaction., program purpose french : The demand for two-way radio communication has increased dramatically and this growth trend is expected to_x000D_
continue. Our industry partner for this project, Tridon Communications, operates a two-way radio_x000D_
communications network and currently it faces the challenge of optimizing the number of radio channels at the_x000D_
different sites in order to maximize the satisfaction of its customers while efficiently utilizing the given total_x000D_
number of radio channels. Also, it lacks a solid methodology to make decisions on network dimensioning and_x000D_
extending the network infrastructure in a cost-effective manner. The proposal is to develop a learning-based_x000D_
method for traffic estimation and admission control for Tridon's two-way radio communication system. This_x000D_
method, which will be delivered to Tridon as a set of algorithms and/or software modules, will be used by_x000D_
Tridon to optimize its network performance by efficiently utilizing the radio channels and controlling_x000D_
admission of the users into the network while satisfying their communication performance requirements. Also,_x000D_
the method will be used for network dimensioning and expansion of the currently deployed system. The project_x000D_
will benefit this Canadian Company to offer two-way radio communication services in a competitive price with_x000D_
customers' satisfaction., agreement title english : Development of a learning-based framework for traffic estimation and admission control in two-way radio communication systems, agreement title french : Development of a learning-based framework for traffic estimation and admission control in two-way radio communication systems, agreement number : EGP, agreement value : 25000.0, 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 2018-2019), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019), 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