基于自适应交叉变异量子免疫信号盲检测算法

Quantum Immune Algorithm Based on Adaptive Crossover-mutation Operator for Blind Signals Detection

提出了基于自适应交叉变异算子的量子免疫信号盲检测方法,所述方法在量子化交叉与变异基础上,引入了基于自适应策略的量子免疫交叉与变异算子,用量子交叉与量子变异进行进化,同时采用了传统免疫算法中交叉和变异算子的策略,以求更好地加强种群的进化程度,仿真结果表明所提出的基于自适应交叉变异算子的量子免疫算法能够有效避免早熟现象,收敛速度更快,相同信噪比条件下误码率更低。

Considering the easy converging to local optimum and slow convergence, an adaptive crossover-mutation operator quantum immune algorithm is proposed to blind detection signals of SIMO system. Based on the quantization crossover and mutation, the adaptive immune crossover and mutation operator are introduced. Using quantum crossover and mutation for evolution enhance the evolution of the population better. Simulation results show that the algorithm can avoid premature phenomenon effectively, need shorter received signals and show high speed to blindly detect signals.