大规模MIMO系统中基于能效最大化的资源联合优化算法

曹海燕; 冯瑞瑞; 方昕; 王秀敏; 许方敏

doi:10.11959/j.issn.1000-0801.2017317

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大规模MIMO系统中基于能效最大化的资源联合优化算法

研究与开发 | 更新时间：2024-06-05

- 大规模MIMO系统中基于能效最大化的资源联合优化算法
- A joint optimization algorithm based on energy efficiency maximization for massive MIMO systems
- 电信科学 2017年33卷第12期页码：84-90
- 作者机构：
  
  1. 杭州电子科技大学通信工程学院，浙江杭州 310018
  2. 中国计量大学信息工程学院，浙江杭州 310018
- 作者简介：
  
  [ "曹海燕（1975-），女，博士，杭州电子科技大学通信工程学院副教授、硕士生导师，主要研究方向为无线通信系统的信道编码、信号检测和LTE物理层标准等。" ]
  [ "冯瑞瑞（1993-），女，杭州电子科技大学通信工程学院硕士生，主要研究方向为无线通信、大规模MIMO系统的能效资源分配。" ]
  [ "方昕（1975-），女，博士，杭州电子科技大学通信工程学院副教授、硕士生导师，主要研究方向为4G/5G物理层算法。" ]
  [ "王秀敏（1963-），女，中国计量大学信息工程学院教授、硕士生导师，主要研究方向为电路与系统、信号处理。" ]
  [ "许方敏（1980-），女，博士，杭州电子科技大学通信工程学院讲师，主要研究方向为先进移动通信系统及其关键技术。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61501158);国家自然科学基金资助项目;The National Natural Science Foundation of China(61379027);浙江省教育厅科学基金资助项目;The Education Department Foundation of Zhejiang Province of China(LY14F010019);浙江省教育厅科学基金资助项目;The Education Department Foundation of Zhejiang Province of China(LQ15F01004)
- DOI：10.11959/j.issn.1000-0801.2017317
  中图分类号： TN911.22
- 网络出版日期：2017-12，
  
  纸质出版日期：2017-12-20
- 稿件说明：
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曹海燕, 冯瑞瑞, 方昕, 等. 大规模MIMO系统中基于能效最大化的资源联合优化算法[J]. 电信科学, 2017,33(12):84-90.

Haiyan CAO, Ruirui FENG, Xin FANG, et al. A joint optimization algorithm based on energy efficiency maximization for massive MIMO systems[J]. Telecommunications science, 2017, 33(12): 84-90.
曹海燕, 冯瑞瑞, 方昕, 等. 大规模MIMO系统中基于能效最大化的资源联合优化算法[J]. 电信科学, 2017,33(12):84-90. DOI： 10.11959/j.issn.1000-0801.2017317.

Haiyan CAO, Ruirui FENG, Xin FANG, et al. A joint optimization algorithm based on energy efficiency maximization for massive MIMO systems[J]. Telecommunications science, 2017, 33(12): 84-90. DOI： 10.11959/j.issn.1000-0801.2017317.

摘要

针对信道条件未知的多小区大规模多输入多输出（MIMO）系统，提出一种对导频序列长度、导频符号功率以及数据符号功率进行联合优化的资源分配算法。采用最大比合并（MRC）接收，考虑电功率和导频污染的影响，并对最大传输功率进行约束从而建立起以能效（EE）最大化为目标的非凸函数模型。根据分数规划的性质，首先将分数形式转化成减式形式，进而分解成一系列凸函数之差（DC）的问题，最后采用交替优化算法联合调整 3 个变量从而达到能效最大化的目标。仿真结果表明，随着最大符号传输功率的增加，所提方案仍然能保持良好系统能效性能。

Abstract

For the massive multi-cell multi-input multiple-output (MIMO) communication uplink system with unknown channel status information

a resource allocation algorithm which jointly optimizes the pilot sequence length

pilot symbol power and data symbol power was proposed.With the maximum ratio combining (MRC) receiver

the influence of circuit power was considered

pilot contamination and the constraint of maximum transmission power

and a nonconvex function modeled with the goal of maximizing energy efficiency (EE) was established.Firstly

the fractional form was transformed into an equivalent subtractive form by using the properties of fractional programming and then decomposed into a series of DC problems

finally

by using an iterative optimization algorithm

the three variables were alternately adjusted with maximizing the energy efficiency.Simulation results show that with the increasing of the maximum symbol transmission power

the proposed scheme can still have the great EE performance for the massive MIMO systems.

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references

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