去蜂窝大规模MIMO-NOMA系统能效优化算法

doi:10.12263/DZXB.20211351

电子学报

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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

华东交通大学电气与自动化工程学院，江西南昌 330013

收稿日期:2021-10-08 修回日期:2022-01-17 出版日期:2023-01-04
- 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.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
- 基金资助:
- 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)

Energy Efficiency Optimization Algorithm for Cell-Free Massive MIMO-NOMA Systems

DING Qing-feng, LI Yi-hao, XU Meng-yin

School of Electrical and Automation Engineering，East China Jiaotong University，Nanchang，Jiangxi 330013，China

Received:2021-10-08 Revised:2022-01-17 Online:2023-01-04
- Supported by:
- National Natural Science Foundation of China (61961018); Jiangxi Province Natural Science Foundation of China (20224ACB202001); Jiangxi Province Postgraduate Innovation Foundation of China (YC2021-S416)

摘要/Abstract

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.

关键词: 非正交多址接入, 用户分组, 功率控制, 连续凸近似

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, 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 was 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.

Key words: NOMA, user grouping, power allocation, SCA

中图分类号:

TN929.5

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, 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, DOI: 10.12263/DZXB.20211351.

图/表 8

图1 去蜂窝大规模MIMO-NOMA系统

表1 仿真参数

参数	数值
$N 0$	$290 × κ × B × N F$
$κ, B, N F$	$1.381 × 10 - 23, 20 M H z, 9 d B$
$τ p, τ c$	$N N O M A, K t o t O M A, 200$
$M, K, L$	$20,2, 15$
$ρ p, ρ d$	$0.1 W, 0.2 W$
$σ s h$	$8 d B$
$D$	$1 k m$
$χ m$	$0.4$
$P t c, m, P 0, m, P c i r$	$0.2 W, 0.825 W, 0.1 W$
$P b t, m$	$0.25 W / G b i t s ⋅ s - 1$

表1 仿真参数

参数	数值
$N 0$	$290 × κ × B × N F$
$κ, B, N F$	$1.381 × 10 - 23, 20 M H z, 9 d B$
$τ p, τ c$	$N N O M A, K t o t O M A, 200$
$M, K, L$	$20,2, 15$
$ρ p, ρ d$	$0.1 W, 0.2 W$
$σ s h$	$8 d B$
$D$	$1 k m$
$χ m$	$0.4$
$P t c, m, P 0, m, P c i r$	$0.2 W, 0.825 W, 0.1 W$
$P b t, m$	$0.25 W / G b i t s ⋅ s - 1$

图2 不同用户分组方案下能量效率随用户数量变化曲线

图3 功率优化算法的能量效率随迭代次数变化曲线

图4 不同功率分配方案下能量效率随AP数量变化曲线

图5 功率优化方案下能量效率随发射功率变化曲线

图6 能量效率随最小用户速度阈值变化曲线

图7 用户下行速率累积分布函数

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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

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