基于量子遗传优化的盲检测算法  

Blind Detection Algorithm Based on Quantum Genetic Optimization

作　　者：蔡晴红[1] 于舒娟[1] 张昀[1] 

机构地区：[1]南京邮电大学电子科学与工程学院,江苏南京210003

出　　处：《计算机技术与发展》2013年第2期57-59,64,共4页Computer Technology and Development

基　　金：国家自然科学基金资助项目(60772060)

摘　　要：量子遗传算法(Quantum Genetic Algorithm)作为量子计算理论和遗传算法原理相结合的一种新兴的全局优化算法,因算法具有寻优能力强、收敛速度快和计算时间短的特点,在许多领域都得到了广泛应用。文中首先给出基于SIMO系统的BPSK发送信号盲检测模型,利用补投影算子构造盲检测优化代价函数,在此基础上利用量子遗传算法进行优化,获得最佳估计序列。算法性能仿真表明,文中提出的基于量子遗传优化的盲检测算法收敛速度快、能够成功实现盲检测,具有一定的应用价值。Quantum genetic algorithm, as the combination of the quantum computing theory and the principle of genetic algorithm, is a new global optimization algorithm,which has stronger capability in the optimization ,faster convergence and shorter time in computing. It has already been widely used in many areas. It proposes a blind equalization model which sends BPSK signal based on SIMO system. Use projection operator of complement to construct the cost function, based on which quantum genetic algorithm is applied to optimize to ob- tain the best sequence of estimation. The algorithm simulation results show that the proposed blind detection algorithm based on quantum genetic optimization has rapid convergence speed, is able to successfully achieve blind detection, has a certain value.

关 键 词：盲检测 量子遗传算法 量子计算 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]