Resource Allocation In OFDMA Systems Based On Non-Cooperative Game Theory

Nowadays, the wireless network’s functionality expand moreover, make the systemmore complex, meanwhile, the service quality requirement of network users are higher thanbefore, and both of it make a big problem in resources allocation whit limited space whilethe resources of radio spectrum is limited. In order to resolve this contradiction, the paperproposes an innovative solution. The main features of the program is the use of thedistributed nature of wireless multi-cell. And then, we design a algorithm base on a modelthat a mobile base station used to be the center of the multi-cell OFDMA system resourceallocation. Because of limited resources, each user selfishly competition to maximize theirown interests, many participants competing for the same target of interest mode, so here theintroduction of a non-cooperative game theory as a basis for algorithm design. Also, becauseof the energy carried by the mobile base station and the user terminal are limited, to eachsub-carrier and the user corresponding to form a transmit units, and then use to the Sigmondfunction as function modules and establish QoS satisfaction to the user and the sub-nonlinear combination of carrier power ratio function as a utility function. We just call it "theeffectiveness of the joint power function". The design ideas in this article is based on theoptimal efficiency of the unit optimal benefits on behalf of the whole systems, is part of theoverall relationship, the total power of the mobile base stations assigned to each subcarrier as themaximum power before the start of the allocation of resources. The goal of the algorithm is asolution of the Nash equilibrium and solving the utility functions, allocate resources accordingly. Areasonable price (payment) factor for algorithm design is set to be Pareto improvement.Finally, use MATLAB simulation diagram analysis and comparison algorithm improvementsbefore and after, and also an existing algorithm. This algorithm is a compromise of the energyconsumption and user QoS requirements is better use in the energy constrained system.