基于混合量化移相器的毫米波大规模MIMO预编码设计
Mixed⁃Resolution Phase Shifters⁃Based Precoding Design for the mmWave Massive MIMO Systems
- 电子学报 2021年49卷第12期 页码：2349-2356
- 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年生于安徽怀宁.现为华东交通大学电气与自动化工程学院教授、硕士生导师.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" ]
[ "罗 静 男,1997年生于江西新余.现为华东交通大学电气与自动化工程学院研究生.主要研究方向为毫米波通信,混合预编码设计.E‑mail：luojing9102@163.com" ]
[ "高鑫鹏 男,1995年生于内蒙古呼伦贝尔.现为华东交通大学电气与自动化工程学院研究生.主要研究方向为中继混合预编码,低复杂度设计.E‑mail：gxinpeng1030@foxmail.com" ]
[ "石 辉 男,1997年生于江西鄱阳.现为华东交通大学电气与自动化工程学院研究生.主要研究方向为智能电网与无线通信." ]
- 基金信息：国家自然科学基金项目(61961018);江西省杰出青年人才计划项目(20192BCB23013);江西省自然科学基金项目(20192ACB21003);江西省研究生创新专项资金资助项目(YC2020‑S324)
DOI：10.12263/DZXB.20201370
中图分类号： TN929.5收稿：2020-12-01，
修回：2021-04-25，
纸质出版：2021-12-25
- 稿件说明：
移动端阅览
丁青锋,罗静,高鑫鹏等.基于混合量化移相器的毫米波大规模MIMO预编码设计[J].电子学报,2021,49(12):2349-2356.
DING Qing-feng,LUO Jing,GAO Xin-peng,et al.Mixed⁃Resolution Phase Shifters⁃Based Precoding Design for the mmWave Massive MIMO Systems[J].ACTA ELECTRONICA SINICA,2021,49(12):2349-2356.
丁青锋,罗静,高鑫鹏等.基于混合量化移相器的毫米波大规模MIMO预编码设计[J].电子学报,2021,49(12):2349-2356. DOI： 10.12263/DZXB.20201370.
DING Qing-feng,LUO Jing,GAO Xin-peng,et al.Mixed⁃Resolution Phase Shifters⁃Based Precoding Design for the mmWave Massive MIMO Systems[J].ACTA ELECTRONICA SINICA,2021,49(12):2349-2356. DOI： 10.12263/DZXB.20201370.
摘要
针对毫米波大规模MIMO（Multiple-Input Multiple-Output）系统能量效率低下的问题
提出一种基于混合精度移相器量化的混合预编码设计方法.首先考虑到系统能量效率闭合表达式难以直接求解
通过Dinkelbach方法将能量效率优化问题转换为范数最小化的形式
然后将其进一步解耦为混合预编码矩阵和混合精度移相器量化配比问题
实现非凸能效低范数和的凸优化转化
最后通过引入酉矩阵松弛恒模约束求解混合预编码矩阵
并采用增量搜索算法求解混合量化移相器精度配比向量
从而实现系统能量效率最大化.仿真结果表明
所提出的混合精度量化算法的系统频谱效率优于传统单精度量化算法
且具有更高的系统能量效率.同时
当多数据流传输时
所提出混合精度量化结构的系统性能接近全数字结构.
Abstract
For the insufficient energy efficiency(EE) in mmWave massive MIMO(Multiple-Input Multiple-Output) systems
a method with mixed-resolution phase shifters is proposed. Considering that the closed expression for EE is difficult to solve directly
the EE optimization problem is converted into norm minimization form through the Dinkelbach method. Then it is further decoupled into the hybrid precoding matrix and the mixed-resolution ratio problems to realize the convex optimization transformation of non-convex EE and low norm sum. Finally
in order to maximize the EE of the system
the unitary matrix relaxation constant modulus constraint is introduced to solve the full-resolution hybrid precoding matrix
and the incremental search algorithm is used to solve the optimal mixed-resolution ratio vector. The simulation results show that the spectrum efficiency performance of the proposed mixed-resolution algorithm is better than that of the traditional finite-resolution algorithm
and it has higher EE performance. Meanwhile
the system performance of the proposed mixed-resolution quantization structure is close to the full-digital structure when multiple data streams are transmitted.
关键词
Keywords
references
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