Research On Game Theory Based Load Balancing Algorithm In LTE System

With the rapid development of communication technology, the demands of users for increasing system capacity become more and more large. At the same time, it is an inevitable trend for future mobile communication systems that there is a need to provide types of services to mobile users. Especially for the next generation wireless network which requires high-speed rate and low-latency, RRM(Radio Resource Management) is the key to improve the system performance and ensure the QoS(Quality of Service). Because of the randomness of the network load, the situation of load congestion is very difficult to completely avoid. And if we only one-sided increase the capacity of network, it will cause the increasing of investment and the devices will be idle, affecting investment returns. Therefore, the rational use of network resources is very significant. Load balancing as a major method of RRM attracts more and more attention. This article makes research in the network load balancing strategies in the background of LTE/LTE-A(Long Term Evolution/Long Term Evolution Advanced).After analyzing the requirement of self-optimizing in LTE system, a game theory based algorithm is proposed. The basic idea of the algorithm is to make game theory combined with load balancing. The article formulates load balancing as market equilibrium and use Fisher model with linear inequalities to solve the problem. The primal-dual interior-point algorithm is used to compute the equilibrium prices. By the setting of transmission powers for base stations, according to the optimal solutions, the traffic load of the network can be transferred reasonably. Simulation results show that compare with the other algorithms, game theory based algorithm can achieve greater system capacity and provide higher system performance. Because the algorithm can get such high-precision power value that the system can effectively reduce energy consumption to achieve Green Communications.