Upgraded-ABC Algorithm for Antenna Selection in Energy Efficient Massive MIMO System

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI:10.1109/ICAECCS56710.2023.10105114

F. Bouchibane, H. Tayakout, N. Ziane, F. Siahmed, S. Hebib

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引用次数: 1

Abstract

Massive MIMO (mMIMO) technology adopted by the fifth generation mobile communication systems and beyond offers high reliability, spectral and energy efficiencies thanks to the big size of antenna and the exploitation of the potential of spatial multiplexing. Increasing the antenna size implies a comparable increase in the Radio Frequency (RF) components number connected to each antenna which involves low energy efficiency due to the high power consumption. Hence, antenna selection aims at reducing this consumption through designating a qualified subset of antennas from the total available ones while maintaining better performance. We compare in this paper three improved versions of Artificial Bee Colony optimization algorithm to identify the set (antenna number, terminal number) that maximizes the relative energy efficiency in a mMIMO system. Upgraded-ABC version has shown high performance compared to the Gbest-guided ABC, 3G-ABC and the original ABC in terms of robustness and time cost.

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节能大规模MIMO系统天线选择的改进abc算法

第五代移动通信系统及以后采用的大规模MIMO (mMIMO)技术由于天线的大尺寸和对空间多路复用潜力的开发，提供了高可靠性、频谱和能源效率。增加天线尺寸意味着连接到每个天线的射频(RF)组件数量的相应增加，这涉及由于高功耗而导致的低能效。因此，天线选择旨在通过从所有可用天线中指定合格的天线子集来减少这种消耗，同时保持更好的性能。在本文中，我们比较了三种改进的人工蜂群优化算法，以确定mMIMO系统中相对能源效率最大的集合(天线数，终端数)。与Gbest-guided ABC、3G-ABC和原始ABC相比，升级版ABC在鲁棒性和时间成本方面表现出了较高的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS)

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