面向6G的用户为中心网络研究综述

施建锋; 杨照辉; 黄诺; 陈晓; 张玉洁; 陈明

doi:10.11999/JEIT220242

面向6G的用户为中心网络研究综述

doi: 10.11999/JEIT220242

施建锋^{1, 2, ,},
杨照辉³,
黄诺⁴,
陈晓¹,
张玉洁⁵,
陈明²

1.
南京信息工程大学电子与信息工程学院南京 210044
2.
东南大学移动通信国家重点实验室南京 211189
3.
伦敦大学学院电子电气工程学院伦敦 E20 3BS
4.
中国科技大学中国科学院无线光通信重点实验室合肥 230027
5.
南京铁道职业技术学院智能工程学院南京 210015

基金项目: 江苏省自然科学基金(BK20210641)，东南大学移动通信国家重点实验室开放研究基金(2021D11, 2022D10)，江苏省高等学校自然科学研究项目(20KJB510037, 21KJB510031)，南京信息工程大学人才启动项目(2020r009)

详细信息

作者简介:
施建锋：男，博士，讲师、研究生导师，研究方向为新一代移动通信网络、天地一体化网络、无线资源管理、凸优化理论等

杨照辉：男，博士，博士后研究员，研究方向为无人机辅助通信、超可靠超低时延通信、边缘计算和非正交多址接入等

黄诺：男，博士，副研究员，研究方向为无线光通信系统的传输设计和无线通信网络的资源分配等

陈晓：女，博士，讲师，研究方向为大规模MIMO无线通信、基于机器学习的无线通信等

张玉洁：女，硕士，讲师，研究方向为绿色能源、新能源电池和智能控制等

陈明：男，博士，教授、博士生导师，研究方向为信号处理、无线资源管理等

通讯作者:
施建锋　jianfeng.shi@nuist.edu.cn

中图分类号: TN929.5
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- 被引次数: 0
出版历程
- 收稿日期: 2022-03-08
- 修回日期: 2022-05-23
- 网络出版日期: 2022-06-01
- 刊出日期: 2023-05-10

A Survey on User-centric Networks for 6G

1.
School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
National Mobile Communications Research Laboratory, Southeast University, Nanjing 211189, China
3.
School of Electrical and Electronic Engineering, University College London, London E20 3BS, UK
4.
CAS Key Laboratory of Wireless-Optical Communications, University of Science and Technology of China, Hefei 230027, China
5.
School of Intelligent Engineering, Nanjing Institute of Railway Technology, Nanjing 210015, China

Funds: The Natural Science Foundation of Jiangsu Province of China (BK20210641), The Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (2021D11, 2022D10), The Natural Science Foundation of the Jiangsu Higher Education Institutions of China (20KJB510037, 21KJB510031), The Startup Foundation for Introducing Talent of NUIST (2020r009)

摘要

摘要: 与第5代移动通信网络(5G)相比，第6代移动通信网络(6G)有望引入新的性能指标和应用方案，如全球覆盖、更高的频谱/能源/成本效率、更高的智能和安全水平。用户为中心网络(UCN)将成为实现6G的关键推动者，因为其突破了传统基站为中心网络并与信息产业的新兴技术形成了有效融合。该文将从物理层的信道估计和预测、网络上层的性能分析以及链路层的无线资源管理等方面综述这一新型网络的研究现状。首先，讨论和分析UCN的概念和总体网络架构；其次，总结UCN网络中信道估计预测方法、性能分析策略和无线资源管理(RRM)方案；最后，在广泛的调研基础上，探讨UCN网络中的开放性问题，为今后的研究方向提供思路。此综述旨在使读者快速而全面地了解UCN的当前技术状况，从而吸引更多的研究人员进入这一领域。
- 用户为中心网络 /
- 信道估计预测 /
- 性能分析 /
- 无线资源管理
Abstract: Compared with the Fifth Generation mobile network (5G), the Sixth Generation mobile network (6G) is expected to introduce new performance indicators and application scenarios. Global coverage, high spectrum/energy/cost efficiency, high level of intelligence and security are leading features in 6G era. Different from traditional Base Station (BS)-centric network, the User-Centric Network (UCN) emerges as a key enabler for 6G by combining emerging technologies from information industries. In this novel framework, a comprehensive overview of physical layer, network layer and link layer is provided. As a starting point, the concepts and general architecture of the UCNs are surveied and discussed. Then, the survey is classified as: channel estimation and prediction; performance analysis with diverse performance metrics; different types of RRM (Radio Resource Management). Finally, based on extensive discussions, open issues are provided to guide future scholarly research directions. It is anticipated that this survey will provide a quick and comprehensive understanding of the current state of the arts for UCNs which attracting more researchers into this area.
- User-Centric Networks (UCN) /
- Channel estimation and prediction /
- Performance analysis /
- Radio Resource Management (RRM)

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图 1 近几年全球移动数据量增长趋势^[1]

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图 2 UCN网络示意图

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图 3 UCN中具有解耦特性的不同场景

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图 4 UCN各层次节点中资源配备示意图

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图 5 UCN中多维无线资源分配示意图

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图 6 物理层无线资源与网络上层资源示意图

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表 1 已有综述工作对比

文献	全面综述	信道估计与预测	性能分析	无线资源管理	贡献
文献[8]	√	×	×	√	CRAN在工业界和学术界的全面综述：物理层和上层无线资源管理方面的关键技术。
文献[9]	√	×	×	×	CRAN体系架构、优势和挑战及其实现。
本文	√	√	√	√	UCN信道估计、性能分析和无线资源管理等方面的全面综述：已有工作总结和未来研究热点探讨。

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表 2 缩略词

缩写	全拼	含义
3GPP	the Third-Generation Partnership Project	第3代伙伴计划
5G	the Fifth Generation mobile network	第5代移动通信网络
6G	the Sixth Generation mobile network	第6代移动通信网络
AP	Access Point	接入节点
BCD	Block Coordinate Descent	块坐标下降
BINLP	Binary Integer Non-Linear Programming	二进制整数非线性优化
CRAN	Cloud Radio Access Network	云接入网
CSI	Channel State Information	信道状态信息
CVSINR	Cluster Virtual Signal-to-Interference-plus-Noise Ratio	群虚拟信干燥比
DeDU	Decoupled Downlink and Uplink	上下行解耦
MISO	Multiple Input Single Output	多输入单输出
MIMO	Multiple Input Multiple Output	多输入多输出
MINLP	Mixed-Integer Non-Linear Programming	混合整型非线性优化
SISO	Single Input Single Output	单输入单输出
TCN	Traditional Cellular Network	传统蜂窝网络
UCN	User-Centric Network	用户为中心网络
UDN	Ultra-Dense Network	超密集网络
WMMSE	Weighted Minimum Mean Square Error	权重最小均方误差

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表 3 UCN与TCN之间的对比

对比内容	网络
对比内容	TCN	UCN
部署范围	较大范围	室内/热点区域
AP密度	低	高
用户密度	远高于AP密度	与AP密度相仿
覆盖特点	异构，不规则形状	单层，规则的蜂窝形状
用户移动性	高	低
速率	中低	高
前传链路	理想的有线链路	理想的有线链路/非理想的无线链路

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表 4 信道估计与预测研究工作总结

类别	文献	方法
基于模型的传统估计预测	文献[15,26]	压缩感知
	文献[18,19,21]	图论
	文献[16,17,20,25,27]	优化理论(松弛、罚函数、BCD)
基于人工智能的新型估计预测	文献[23,24,30-35]	深度神经网络(循环神经网络、卷积神经网络)
基于人工智能的新型估计预测	文献[28,29,34,35]	长短时记忆网络

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表 5 性能分析研究工作总结

性能指标类别	场景	文献	方法
概率类(覆盖概率、中断概率和用户接入概率等)	SISO	文献[36]	随机几何
	SISO	文献[37]	级数逼近
	DeDU	文献[48]	随机几何
容量类(中断容量、遍历容量和用户数据速率等)	SISO	文献[38-40]	随机几何
容量类(中断容量、遍历容量和用户数据速率等)	MIMO	文献[44,45]	分布逼近
综合类(能效和切换率等)	SISO	文献[47]	随机几何

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表 6 无线资源管理研究工作总结

类别	资源种类	文献	方法
单维资源管理	功率资源	文献[49-52]	交替迭代、凸优化理论、深度Q学习网络
	计算资源	文献[54,55]	深度强化学习、合作博弈理论
	训练资源	文献[53]	图论
2维资源管理	子载波&功率	文献[56,57]	分支切割、交替迭代
	链路容量&计算	文献[58]	松弛近似、罚函数
	比特&计算	文献[58,59]	线性优化理论、循环神经网络
	波束方向&功率	文献[60-62]	松弛近似、深度Q学习网络
3维资源管理	子载波、功率&比特	文献[63]	交替迭代
	用户调度、子载波&功率	文献[64,65]	交替迭代、粒子群算法、松弛近似
	比特、波束方向&功率	文献[66]	深度学习神经网络
	AP集群、波束方向&功率	文献[67-72]	粒子群算法、凸优化理论、松弛近似、WMMSE、深度残差学习网络、深度神经网络
	导频、波束方向&功率	文献[73]	信号处理理论、松弛近似
4维资源管理	计算、存储、波束方向&功率	文献[74]	松弛近似、交替迭代
	AP集群、传输时隙、波束方向&功率	文献[75]	松弛近似、凸优化理论
	AP集群、前传链路压缩比、波束方向&功率	文献[76]	范数最小化、凸优化理论
	用户调度、AP集群、子载波&功率	文献[77]	交替迭代、协同优化理论

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