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Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

机译:基于遗传算法的合作蜂窝网络中近乎最优的资源分配

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摘要

This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implemented to guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genetic algorithm can approximately achieve the optimum bandwidth efficiency whilst requiring only 24% of the computation effort of the exhaustive search in the investigated network.
机译:本文说明了如何将遗传算法用作获得协作蜂窝网络中资源块调度问题的最佳解决方案的方法。最初执行穷举搜索以确保找到最佳结果,以最大程度地提高整个网络的带宽效率,然后在同一网络中使用具有正确选择的终止条件的遗传算法。仿真结果表明,该遗传算法在被调查网络中仅需要穷举搜索的24%的计算工作量,即可大致实现最佳带宽效率。

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