认知无线网络中基于免疫克隆优化的功率分配

Power Allocation of Cognitive Wireless Network Based on Immune Clonal Optimization

针对认知OFDM无线网络中下行链路的功率分配问题,将其建模为一个约束优化问题,进而提出了一种基于免疫克隆的求解方法。给出了功率分配的数学优化模型、算法实现过程和关键技术,设计了适合算法求解的编码、克隆、变异算子。仿真实验结果表明,在总发射功率、误码率及主用户可接受的干扰约束下,该算法可以获得更大的总数据传输率,同时具有较快的收敛速度,能够得到较优的功率分配方案,进而提高频谱利用效率。

The optimization of downlink power allocation of cognitive OFDM wireless network is converted into an optimization problem with constraints. An immune clonal algorithm is proposed to solve this problem. The power allocation model, key techniques, and implementation processes are described. The coding, clonal, and maturation operators are designed. The experiments results show that, with the constraints of total power, the bit error rate （BEg） and the acceptable interferences of primary user, the algorithm can maximizes the total transmit rate and converges rapidly. It can get the better power allocation scheme and improve the reuse of spectrum.