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Optimal Cooperative Virtual Multi-input and Multi-output Network Communication by Double Improved Ant Colony System and Genetic Algorithm

机译:双改进蚁群系统和遗传算法的最优协同虚拟多输入多输出网络通信

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This paper we research on the problem of cooperative virtual multi-input and multi-output (MIMO) network communication distance under the assumption of nodes placed along an appointed direction. The objective here is to choose the parameters value to solve this model based on the double improved ant colony system (DIACS) and genetic algorithm (GA) to optimize the set of relays to satisfy the outage probability constraint We use experimental analyses to carry out the reasonable selection value of all the parameters in the algorithm. The simulation experiments compared during DIACS with Ant Colony System (ACS) and particle swarm optimization (PSO) algorithms, the simulation results proves DIACS is effective, and has an advantage of high accuracy and time saving especially when optimize the parameters' value, and the results are better than the other two algorithms.
机译:本文研究了节点沿指定方向放置的情况下虚拟多输入多输出(MIMO)网络的协作通信距离问题。这里的目的是基于双重改进蚁群系统(DIACS)和遗传算法(GA)选择参数值来求解该模型,以优化继电器集以满足停电概率约束。我们使用实验分析来进行算法中所有参数的合理选择值。将DIACS与蚁群系统(ACS)和粒子群优化(PSO)算法进行了仿真实验,仿真结果证明DIACS是有效的,并且具有高精度和省时的优势,特别是在优化参数值时,以及结果优于其他两种算法。

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