Sharing of network resources in next generation wireless communication systems

Abstract

Recent years have witnessed many research in the area of wireless networks. The goals can be divided into two main categories: improving network performance and energy efficiency. Game theory is widely used to relate the behavior of the users therefore, the cooperation among nodes can be achieved and network performance can be improved when the game theory is utilized. The applications of mathematical analysis to the study of wireless ad hoc networks have met with limited success due to the complexity of mobility and traffic models, the dynamic topology, and the unpredictability link quality that characterize such networks. The ability to model individual, independent decision-makers whose actions potentially affect all other decision-makers renders game theory particularly attractive to analyze the performance of the ad hoc networks. The cooperative approach with the use of game theory can achieve power minimization, yet presents overheads, while non-cooperative solutions utilizing the game theory reduce overhead, yet taking more iterations as well as power for convergence. The dissertation suggests a new game theorybased algorithm for achieving trade-offs between communication overhead and the power control with regard to multiple antenna enabled wireless adhoc networks that operate in multiple-user interference environments. Enhanced joint iterative power adaptions in addition to the beamforming approach has been developed for minimizing mutual interferences at each one of the wireless nodes along with constant received Signal to Interference Noise Ratio (SINR) at each one of the receiver nodes. The performance optimization method has presented the comparison between suggested algorithms and COPMA and Regret Matching based joint transmit beamformer and power Selection Game (RMSG) is provided. Furthermore, simulation results related to the two approaches proving effective power adaptions as well as beamforming with regard to large and small networks with minimum interferences and overheads in comparison to modern approaches. Complexity analysis is presented, the comparison between different games are presented.