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基于量子粒子群算法的MIMO信道容量优化 被引量:1

On Capacity Optimization for MIMO Channel Based on Quantum-behaved Particle Swarm Optimization Algorithm
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摘要 MIMO技术是一种很有潜力的新一代无线通信领域的关键技术,其高信道容量是最具吸引力的地方,但是其信道容量的实现受到多种因素的影响。综合考虑影响其容量的各个环节,仔细分析了其中几个关键因素并给出了相应的仿真。为了最大限度地实现高信道容量,依据量子粒子群优化算法,结合理论分析给出了惩罚函数,并构造了基本粒子,这样根据迭代函数就可以求出最佳粒子,依照此最佳粒子就可以合理优化设计MIMO系统。 MIMO (Multiple Input Multiple Output), as the key technology of next generation wireless communication,is very promising. Its high channel capacity is the most attractive aspect,however,many factors will affect its realization. These factors , which have big influence on MIMO channel capaci- ty, are taken into account in this paper. Some of these factors are also analyzed attentively and at the same time, the simulations are given. In order to obtain the maximized channel capacity, quantum-behaved particle swarm optimization algorithm is used. The penalty function is obtained according to the theoretical analysis. Meanwhile, the basic particles are built. Thus, the optimal particle is obtained through the iterated function. Lastly, the optimal MIMO system could be designed according to the optimal particle.
出处 《电视技术》 北大核心 2012年第23期76-78,82,共4页 Video Engineering
基金 江苏省科技支撑计划项目(BE2011501)
关键词 信道容量 影响因素 量子粒子群算法 惩罚函数 channel capacity factors quantum-behaved particle swarm optimization algorithm penalty function
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