Development of a learning-based framework for traffic estimation and admission control in two-way radio communication systems

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The demand for two-way radio communication has increased dramatically and this growth trend is expected tocontinue. Our industry partner for this project, Tridon Communications, operates a two-way radiocommunications network and currently it faces the challenge of optimizing the number of radio channels at thedifferent sites in order to maximize the satisfaction of its customers while efficiently utilizing the given totalnumber of radio channels. Also, it lacks a solid methodology to make decisions on network dimensioning andextending the network infrastructure in a cost-effective manner. The proposal is to develop a learning-basedmethod for traffic estimation and admission control for Tridon's two-way radio communication system. Thismethod, which will be delivered to Tridon as a set of algorithms and/or software modules, will be used byTridon to optimize its network performance by efficiently utilizing the radio channels and controllingadmission of the users into the network while satisfying their communication performance requirements. Also,the method will be used for network dimensioning and expansion of the currently deployed system. The projectwill benefit this Canadian Company to offer two-way radio communication services in a competitive price withcustomers' satisfaction.