认知网络中基于博弈论的联合功率控制与速率分配算法

针对认知无线网络上行链路中的资源分配问题，提出了一种适应于多小区认知无线网络的基于功率控制与速率分配的博弈算法。为了更加合理地控制用户的功率和速率，减小各次用户间的干扰，首先，在效用函数中分别给功率和速率设置了不同的代价因子，使其能够更加合理地控制用户，避免用户过度增加发射功率。其次，从理论上证明了该算法纳什均衡的存在性、唯一性以及算法的收敛性。最后，为了解决发射功率和传输速率的最优化问题，给出了联合功率控制和速率分配的迭代更新算法流程图。理论分析及仿真结果表明，与同类博弈算法相比，在保证通信质量的前提下，所提算法可以使得用户以较小的发射功率获得较大的传输速率和较高的信干噪比（SINR），并且减小了用户间的干扰，提高了次用户系统容量。

Game-theoretic algorithm for joint power control and rate allocation in cognitive networks

Aiming at the resource allocation problem for the uplink in cognitive radio networks, a game-theoretic algorithm for joint power control and rate allocation adapted to multi-cell cognitive radio networks was proposed. To control user's power and rate more reasonably and reduce interference among Secondary Users (SUs), firstly, the different cost factors for power and rate were set respectively, so as to control user more reasonably and avoid user excessively increasing transmission power. Then, the existence and uniqueness of the Nash Equilibrium (NE) for the proposed algorithm were proved, the convergence demonstration of the proposed algorithm was given. Finally, for solving the optimization problem of the transmission power and transmission rate, the iterative updating flowchart of the proposed algorithm for the joint power control and rate allocation was presented. The theoretical analysis and simulation results show that, compared with the similar game algorithms, on the premise of guaranteeing the quality of communication, the proposed algorithm can make user acquire higher transmission rate and higher Signal to Interference plus Noise Ratio (SINR) at lower transmission power, reduce the interference among users, and improve the system capacity of SUs.