去蜂窝大规模MIMO-NOMA系统能效优化算法

丁青锋; 李怡浩; 徐梦引

doi:10.12263/DZXB.20211351

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去蜂窝大规模MIMO-NOMA系统能效优化算法

学术论文 | 更新时间：2025-12-08

- 去蜂窝大规模MIMO-NOMA系统能效优化算法
- Energy Efficiency Optimization Algorithm for Cell-Free Massive MIMO-NOMA Systems
- 电子学报 2023年51卷第8期页码：2020-2029
- 作者机构：
  
  华东交通大学电气与自动化工程学院，江西南昌 330013
- 作者简介：
  
  [ "丁青锋男，1980年出生，安徽怀宁人.现为华东交通大学电气与自动化学院教授，博士生导师.主要研究方向为轨道交通无线通信、智能优化、下一代无线通信技术等.中国电子学会会员：E190027076M.E-mail: brandy724@sina.com" ]
  [ "李怡浩男，1999年出生，安徽安庆人.现为华东交通大学电气与自动化工程学院硕士研究生.主要研究方向为去蜂窝大规模MIMO通信.E-mail: liyih666@163.com" ]
  [ "徐梦引女，1996年出生，湖北天门人.现为华东交通大学电气与自动化工程学院硕士研究生.主要研究方向为去蜂窝大规模多输入多输出系统.E-mail: xumy1016@foxmail.com" ]
- 基金信息：
  
  国家自然科学基金(61961018);江西省杰出青年人才计划(20192BCB23013);江西省自然科学基金(20192ACB21003);江西省研究生创新资金(YC2021-S416)
- DOI：10.12263/DZXB.20211351
  中图分类号： TN929.5;
- 收稿：2021-10-08，
  
  修回：2022-01-17，
  
  纸质出版：2023-08-25
- 稿件说明：
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丁青锋,李怡浩,徐梦引.去蜂窝大规模MIMO-NOMA系统能效优化算法[J].电子学报,2023,51(08):2020-2029.

DING Qing-feng,LI Yi-hao,XU Meng-yin.Energy Efficiency Optimization Algorithm for Cell-Free Massive MIMO-NOMA Systems[J].ACTA ELECTRONICA SINICA,2023,51(08):2020-2029.
丁青锋,李怡浩,徐梦引.去蜂窝大规模MIMO-NOMA系统能效优化算法[J].电子学报,2023,51(08):2020-2029. DOI： 10.12263/DZXB.20211351.

DING Qing-feng,LI Yi-hao,XU Meng-yin.Energy Efficiency Optimization Algorithm for Cell-Free Massive MIMO-NOMA Systems[J].ACTA ELECTRONICA SINICA,2023,51(08):2020-2029. DOI： 10.12263/DZXB.20211351.

摘要

针对去蜂窝大规模多输入多输出（Multiple-Input Multiple-Output，MIMO）非正交多址接入（Non-Orthogonal Multiple Access，NOMA）系统能耗较大的问题，提出一种兼顾功率消耗和用户服务质量的能效优化算法.首先建立下行链路总能效最大化的资源分配模型，将该非凸能效优化问题分解为用户分组和功率分配两个子问题，然后利用统计学理论提出最大化信道增益差与最小化信道相关度的用户分组算法.基于分组结果，利用连续凸近似法将原非凸功率分配子问题转化为凸优化问题，求解得到最优的功率分配因子.仿真结果表明，与传统的正交多址接入系统相比，应用所提算法的NOMA系统可以获得更高的能效性能和用户吞吐量性能，同时有效提升用户公平性.

Abstract

Aiming at the problem of high energy consumption for non-orthogonal multiple access (NOMA) based cell-free massive multiple-input multiple-output (MIMO) system

a energy efficiency optimization algorithm considering both power consumption and users' quality of service is proposed. A total downlink energy efficiency maximization resource allocation model is formulated

the non-convex energy efficiency optimization problem is decomposed into two sub-problems of user grouping and power allocation

and the user grouping algorithm that maximizes the channel gain difference and minimizes the channel correlation is proposed by using the statistical theory. Based on the grouping result

the non-convex power allocation sub-problem is transformed into a convex one by using the successive convex approximation (SCA) method. Simulation results show that

NOMA system with the proposed algorithm can obtain higher energy efficiency performance and user throughput performance compared with traditional orthogonal multiple access (OMA) system

and effectively improve user fairness.

关键词

Keywords

references

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