应用智能优化技术估计大规模MIMO系统频谱效率-能量效率权衡的Pareto最优前沿

B. K. Gül, N. Taspinar
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引用次数: 0

摘要

随着资源短缺问题日益严重,节能变得越来越重要。这种情况将高能效提上了蜂窝通信领域的议事日程,就像在许多其他领域一样。然而,能量效率的提高会导致频谱效率的降低,从而降低了对小区通信极其重要的面积吞吐量。针对该问题提出的解决方案之一是大规模多输入多输出系统的频谱效率-能源效率优化。在本文中,确定的参数的最优值,其中发挥了关键作用的上述权衡的智能优化已被检查。这些值与真正的帕累托最优前沿进行了比较。与多目标差分进化算法和多目标粒子群算法相比,多目标萤火虫算法的求解结果更为成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Usage of Intelligent Optimization Techniques for Estimation of Pareto Optimal Front of Spectral Efficiency-Energy Efficiency Trade-off in Massive MIMO Systems
Energy saving is gaining importance since the deficiency of resources become more critical day by day. This situation brings high energy efficiency to the agenda in the field of cellular communication, as in many other fields. However, the increase in energy efficiency leads to a decrease in the spectral efficiency, thus reducing the area throughput, which is extremely important for cell communication. One of the solutions suggested to this problem is spectral efficiency-energy efficiency optimizations in massive multi-input multi-output systems. In this paper, the determination of the optimum values of the parameters that which play a key role for the aforementioned trade-off by intelligent optimizations has been examined. These values have been compared with true Pareto Optimal Front. The results obtained with the multi-objective firefly algorithm have been more successful than the results obtained with the multi-objective differential evolution algorithm and multi-objective particle swarm optimization.
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