为了优化认知无线电网络中多用户正交频分复用子载波的资源分配,将其转换为一个约束优化问题,进而提出了一种基于混沌免疫优化的求解方法.给出了算法的实现过程和关键技术,设计了适合算法求解的编码、克隆、重组、变异算子.实验结果表明,在满足认知用户速率、所需误码率及干扰约束的条件下,本文所用算法减小了整个系统所需的总发射功率,同时收敛速度较快,能够得到较优的子载波分配方案,进而提高频谱利用效率. In order to optimize the resource allocation of multi-user orthogonal frequency division multiplexing subcarriers in a cognitive radio network, the problem is transformed into a constrained optimization problem, and then a solution method based on chaotic immune optimization is proposed. The implementation of the algorithm is given And key technologies, we designed encoding, cloning, recombination and mutation operators that are suitable for algorithm solving.The experimental results show that the algorithm used in this paper reduces the entire The total transmit power required by the system, meanwhile, converges at a faster rate, and a better subcarrier allocation scheme can be obtained, thereby improving the spectrum utilization efficiency.