认知无线电中基于非合作博弈的功率分配方法

提出了一种适合于认知无线电网络的功率控制方法．基于信扰比的代价函数,借助兼顾认知用户公平性的惩罚因子，构造一种新的支付函数．基于该支付函数提出了一种非合作博弈功率控制模型．结合博弈理论，证明了该博弈模型纳什均衡解的存在性和惟一性，同时得出该纳什均衡解是帕累托最优的．仿真结果表明，基于该博弈模型功率分配方法收敛性比传统算法好，通过设置合适的惩罚因子等参数，3~5次迭代即可收敛，满足系统实时性要求，同时系统通过量较传统算法有1~4倍的改善．

Power allocation based on noncooperative game theory in cognitive radio

A power allocation method based on the Non-cooperative Power Control Game (NPCG) in cognitive radio networks is proposed. With the concept of pricing factor, a novel cost function based Signal-to-Interference and Noise Ratio (SINR) is as well as a new payoff function designed. By the principle of game theory, we prove the existence and unique of Nash Equilibrium (NE) in our payoff function, and the NE is Pareto Efficiency. Simulation results show that our algorithm is robust and rapid in convergence. By setting an appropriate pricing factor and some other parameters, our algorithm will converge to an NE in about 3~5 iterative operations which can satisfy the real-time requirement. Meanwhile, the throughput of our algorithm is 1~4 times greater than that of the traditional algorithm.