变速度离散粒子群优化算法在盲检测中的应用

Yite Xu, DazhenYe
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引用次数: 1

摘要

本文将连续粒子群优化(PSO)模型扩展到离散粒子群优化(DPSO),在分析传统粒子群优化模型的基础上给出了离散粒子群优化模型,并利用源于粒子速度分析的离散粒子群速度可调机制,提出了一种基于速度可调机制的离散粒子群优化算法。并结合盲序列有限字母的性质来解决直接盲序列检测问题。仿真结果表明,与传统方法和其他直接盲序列检测方法相比,该方法具有更强的直接性和鲁棒性,且不受信道特性的限制,具有良好的检测性能
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Application of Velocity-Changeable Discrete Particle Swarm Optimization Algorithm for Blind Detection
This paper extended the model of continue particle swarm optimization (PSO) to discrete particle swarm optimization (DPSO) and gave its model on the basis of the analysis of conventional PSO, and, moreover, proposed a DPSO algorithm based on a velocity-changeable tunability mechanism by employing the tunable velocity of DPSO originated from the analysis of the velocity of particles, and combined with the property of a finite alphabet of blind sequence to solve the problem of direct blind sequence detection. Simulations demonstrate that this method is characterized with stronger directness and robustness compared with traditional methods and other direct blind sequence detection method and does not suffer from the limit of characteristics of channels and obtains good performance
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