Joint utility-based uplink power and rate allocation in wireless networks: A non-cooperative game theoretic framework |
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| Institution: | 1. School of Automation, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, PR China;2. School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi 710071, PR China;1. Department of Business Administration at Bilkent University, Ankara, Turkey;2. Ministry of Energy and Natural Resources, Ankara, Turkey;1. Federal Institute of Technology of Mato Grosso, MT 235 highway km 12, s/n, Campo Novo do Parecis, MT 78360-000, Brazil;2. Federal Institute of Technology of Piaui, DIASPA, 1597, Centro, Teresina, PI 64018-000, Brazil;3. Infoway e-Healthy Company, R. Antônio Tito, 223, Noivos, Teresina, PI 64045-040, Brazil;4. Institute of Computation, Fluminense Federal University, Av. General Milton Tavares de Souza, s/n, Room 417, São Domingos, Niterói, RJ 24210-346, Brazil;5. Federal University of Rio Grande do Norte, Department of Production Engineering, Technology Center, Room 48, P.O. Box 1551, Lagoa Nova District, Natal, RN, Brazil |
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| Abstract: | In this paper a novel utility-based game theoretic framework is proposed to address the problem of joint transmission power and rate allocation in the uplink of a cellular wireless network. Initially, each user is associated with a generic utility function, capable of properly expressing and representing mobile user’s degree of satisfaction, in relation to the allocated system’s resources for heterogeneous services with various transmission rates. Then, a Joint Utility-based uplink Power and Rate Allocation (JUPRA) game is formulated, where each user aims selfishly at maximizing his utility-based performance under the imposed physical limitations, and its unique Nash equilibrium is determined with respect to both variables, i.e. uplink transmission power and rate. The JUPRA game’s convergence to its unique Nash equilibrium is proven and a distributed, iterative and low complexity algorithm for computing JUPRA game’s equilibrium is introduced. The performance of the proposed approach is evaluated in detail and its superiority compared to various state of the art approaches is illustrated, while the contribution of each component of the proposed framework in its performance is quantified and analyzed. |
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