基于遗传算法的认知无线电网络共同信道和功率最优分配

Power and Channel Optimal Allocation for Cognitive Radio Networks Based on Genetic Algorithm

信道分配和功率控制问题是认知无线电网络中的核心问题。文中根据不完美频谱感知情形下的干扰功率模型,建立认知无线电网络共同信道和功率分配优化模型,并通过罚函数法,将标称的混合整数规划问题简化为不带约束条件的非线性规划问题,提出了基于遗传算法的共同信道和功率最优分配算法。仿真结果表明,该算法能在不完美频谱感知情形下对信道和功率进行联合最优分配,减少对主用户功率干扰,实现网络中认知用户吞吐量的最大化。

Power control and channel allocation are central issues in the cognitive radio networks. Based on interference power model under imperfect spectrum sensing, an optimal mathematical model for com- mon channel and power allocation is presented in this paper. The model is a mixed integer program and difficult to get a numerical resolution. So, an intelligent optimal allocation approach is proposed to over- come this difficulty. Firstly, using penalty function to simplify the mathematical model, a nonlinear pro- gramming function without constrains can be obtained. Then, an optimal allocation approach based on ge- netic algorithm is presented. The proposed concept is evaluated by a simulation example. The simulation results demonstrate that the proposed algorithm can achieve the jointly optimal allocation for power control and channel resource, reduce the power interference for the primary user, and reach the maximum throughput of cognitive users under imperfect spectrum sensing.