Multi-Objective Optimization in 5G Wireless Networks With Massive MIMO

被引：27

作者：

Goudos, Sotirios K. ^{[1
]}

Diamantoulakis, Panagiotis D. ^{[2
]}

Karagiannidis, George K. ^{[2
]}

机构：

[1] Aristotle Univ Thessaloniki, Dept Phys, Thessaloniki 54124, Greece

[2] Aristotle Univ Thessaloniki, Dept Elect & Comp Engn, Thessaloniki 54124, Greece

来源：

IEEE COMMUNICATIONS LETTERS | 2018年 / 22卷 / 11期

关键词：

5C; cellular network; MIMO communications; energy efficiency; optimization techniques;

D O I：

10.1109/LCOMM.2018.2868663

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

The integration of massive multiple-input multiple-output systems in the fifth generation (5G) of wireless networks requires the simultaneous consideration of several conflicting objectives, in order to achieve optimal performance and operation. In this letter, we present a complete optimization framework, which is based on multi-objective evolutionary algorithms (MOEAs), namely, non-dominated sorting genetic algorithm-II and speed-constrained multi-objective particle swarm optimization. In addition, we use a decision maker for the selection of a solution vector that achieves the best compromise solution. The results illustrate that MOEAs are particularly promising techniques for solving such multi-objective problems in 5G networks.

引用

页码：2346 / 2349

页数：4

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