【摘 要】
：
为利用最少的基站数实现规定的服务质量 ,对无线通信网的基站位置进行优化 ,是一个 NP难题 .针对一个区域 ,提出了在 k个备选的位置中选择合适组合的粗粒度并行遗传算法 ,在
【机 构】
：
清华大学自动化系,清华大学自动化系 北京100084,北京100084
论文部分内容阅读
为利用最少的基站数实现规定的服务质量 ,对无线通信网的基站位置进行优化 ,是一个 NP难题 .针对一个区域 ,提出了在 k个备选的位置中选择合适组合的粗粒度并行遗传算法 ,在不提高成本的同时 ,优化网络的覆盖率 .不但提出了一种高效的局部搜索算子 ,而且比较了子群体连接拓扑对优化质量的影响 .仿真证明 ,优化效果超过了已有的算法 .
In order to achieve the required quality of service with a minimum number of base stations and optimize the location of the base station in the wireless communication network, it is an NP problem. For a region, a coarse-grained parallel genetic algorithm that chooses an appropriate combination among k alternative locations , Not only increases the cost but also optimizes the coverage of the network.It not only presents an efficient local search operator but also compares the influence of subgroup connection topology on the optimization quality.The simulation results show that the optimization effect surpasses the existing algorithms .
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