基于HSDPA混合群集智能算法的多用户调度

传统的基于粒子群最优化的混合启发式算法和模拟退火算法往往以牺牲解的质量或者求解速度来实现有效的调度，为了解决这一问题，提出了一种基于高速下行分组接入（HSDPA）标准的混合群集智能算法。首先假定HSDPA标准所指定的是现实性不完善的信道状态信息（CSI）反馈，并以有限集合的形式存在于信道指示符（CQI）中；接着在最优化过程中，利用模拟退火算法和粒子群最优化算法各自的优点设计混合群集智能算法；最后利用混合算法进行数据处理，得到最优解的同时降低了复杂度，从而实现提升系统通量，达到调度最优化的目的。实验结果表明，与传统的基于粒子群最优化的算法相比，所提的混合算法取得了更好的调度效果。

Multi-user scheduling based on hybrid swarm intelligence algorithm with HSDPA

Traditional hybrid heuristic algorithm based on particle swarm optimization algorithms and simulated anneal-ing algorithms are always at the expense of quality or speed for effective scheduling. So a hybrid swarm intelligence algo-rithm based on High Speed Downlink Packages Access（HSDPA）standards is proposed. More realistic imperfect Channel State Information（CSI）feedback in the form of a finite set of Channel Quality Indicator（CQI）values is firstly assumed as specified in the HSDPA standard. Then, the individual of advantages of simulation annealing algorithm and particle swarm optimization algorithm are used to design a hybrid swarm intelligence algorithm in the process of optimization. Finally, the hybrid algorithm for data processing gets the optimal solution while reducing complexity, so as to improve sys-tem throughput and achieve the purpose of scheduling optimization. Experimental results indicate that the hybrid approach achieves a better scheduling result comparing with algorithms based on particle swarm optimization.