Cell-Free Massive MIMO for Future Wireless Networks

面向未来无线网络的无蜂窝大规模 MIMO

• 批准号: EP/X013162/1
• 负责人: Pei Xiao
• 金额: $ 72.77万
• 依托单位: University of Surrey
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX013162%2F1
• 关键词: Cell; Free; Massive; MIMO; Future

To support a wide range of envisioned applications, including autonomous vehicles, the Internet of Things, and immersive technologies, future wireless technologies must meet demanding requirements for higher spectral and energy efficiency, lower end-to-end latency and massive connectivity as well as uniform user experience. Given the constraints on the available resources, the current inflexible, network-centric cellular networks cannot fulfil those disparate performance objectives. Even in massive MIMO cellular systems there remains an inherent bottleneck for cell-edge users. The recently emerged cell-free massive MIMO (CF-mMIMO) concept is a game changer and represents a paradigm shift in the network architecture. In CF-mMIMO, cell boundaries are removed by distributing a large number of centrally connected access points over a wide service area: the resulting global network becomes fully user-centric and flexible. This provides important potential benefits, including: 1) high quality uniform user experience due to the user-centric approach; 2) superior spectral and energy efficiency through joint processing; 3) reduced latency due to distributed processing; 4) exceptional coverage probability due to distributed access points. However, there are key challenges that need to be addressed to realise these underlying benefits of CF-MaMIMO. These challenges constitute major obstacles to keep CFmMIMO from being practically deployable. This research project aims to address those fundamental challenges. The proposed techniques will transform CF-MaMIMO into a fully user-centric, scalable, flexible system to embrace emerging AI-empowered technologies. This will enable CF-MaMIMO to support the wide range of envisioned applications in 6G and beyond. This project will benefit from strong industrial support from BT and ZTE as well as from world-leading international advisory group.

为了支持包括自动驾驶汽车、物联网和沉浸式技术在内的广泛应用，未来的无线技术必须满足更高的频谱和能源效率、更低的端到端延迟和大规模连接以及统一的用户体验等苛刻要求。考虑到对可用资源的约束，当前不灵活的以网络为中心的蜂窝网络不能满足那些不同的性能目标。即使在大规模MIMO蜂窝系统中，对于小区边缘用户仍然存在固有的瓶颈。最近出现的无小区大规模MIMO（CF-mMIMO）概念是一个游戏规则的改变者，代表了网络架构的范式转变。在CF-mMIMO中，通过在广泛的服务区域分布大量集中连接的接入点来消除小区边界：由此产生的全球网络变得完全以用户为中心和灵活。这提供了重要的潜在好处，包括：1）以用户为中心的方法提供了高质量的统一用户体验; 2）通过联合处理实现了上级频谱和能源效率; 3）由于分布式处理，降低了延迟; 4）由于分布式接入点，卓越的覆盖概率。然而，要实现CF-MaMIMO的这些潜在优势，还需要解决一些关键挑战。这些挑战构成了CFmMIMO实际部署的主要障碍。本研究项目旨在解决这些根本性挑战。所提出的技术将把CF-MaMIMO转变为一个完全以用户为中心的、可扩展的、灵活的系统，以拥抱新兴的人工智能技术。这将使CF-MaMIMO能够支持6 G及以后的广泛应用。该项目将受益于英国电信和中兴通讯以及世界领先的国际咨询集团的强大工业支持。

项目成果

Uniform-Distributed Constellation Codebook Design for High-Capacity Visible Light Communications

• DOI: 10.1109/lcomm.2023.3316453
• 发表时间: 2023-11
• 期刊: IEEE Communications Letters
• 作者: Lisu Yu;Jiajia Qian;Yiming Gui;Zilong Liu;Pei Xiao;Yuhao Wang;Zhenghai Wang

Multi-IRS Assisted Multi-Cluster Wireless Powered IoT Networks

• DOI: 10.1109/twc.2022.3228017
• 发表时间: 2023-07
• 期刊: IEEE Transactions on Wireless Communications
• 影响因子: 10.4
• 作者: Zheng Chu;Pei Xiao;D. Mi;Wanming Hao;Yue Xiao;Lie-liang Yang

Deep Reinforcement Learning-Based Sum Rate Fairness Trade-Off for Cell-Free mMIMO

• DOI: 10.1109/tvt.2022.3230041
• 发表时间: 2023-05
• 期刊: IEEE Transactions on Vehicular Technology
• 影响因子: 6.8
• 作者: M. Rahmani;M. Bashar;M. Dehghani;A. Akbari;Pei Xiao;R. Tafazolli;M. Debbah

IRS-Assisted Wireless Powered IoT Network With Multiple Resource Blocks

• DOI: 10.1109/tcomm.2023.3242365
• 发表时间: 2023-04
• 期刊: IEEE Transactions on Communications
• 影响因子: 8.3
• 作者: Zheng Chu;Pei Xiao;D. Mi;Wanming Hao;Qingchun Chen;Yue Xiao

Energy-Efficient Task Offloading in RIS-Aided HetNets With Wireless Backhaul

• DOI: 10.1109/lcomm.2023.3299380
• 发表时间: 2023-09
• 期刊: IEEE Communications Letters
• 作者: Li Zhang;Jinping Niu;Yiyao Wang;Gaojie Chen;Tao Gu;Yanyan Li