Analysis and Design for Cell-Free Massive MIMO

无蜂窝大规模MIMO分析与设计

• 批准号: MR/S017666/1
• 负责人: Hien Ngo
• 金额: $ 86.23万
• 依托单位: Queen's University Belfast
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FS017666%2F1
• 关键词: Analysis; Design; Cell; Free; Massive

Demand for wireless traffic (data traffic and the number of connected devices) has grown exponentially. With the dramatic growth of wireless devices (such as smart-phones, tablets, and laptops) and services/applications (such as real-time video calls, high-quality movies, real-time 3D games, and Internet of Things), the wireless traffic demand will continue to gain momentum. According to Cisco, global mobile data traffic will reach 43 Exabyte per month by 2021, which is about a 7-fold increase over 2016, and a 3-fold increase over 2018. By 2021, there will be 11.6 billion mobile-connected devices, which corresponds to 1.5 devices per capita. In addition, there is growing concern about green communications (low energy radiation/consumption), security and privacy. To summarize, future wireless networks have to satisfy the following requirements: (1) manage at the same time many (thousands or even millions) devices; (2) each needs a high throughput (spectral efficiency) to support many services/applications; (3) high energy efficiency; and (4) high-level security services.Mobile network is one of the core networks in wireless communications. In conventional mobile networks, a coverage area is divided into cells. Each cell is served by one base station. We have seen many revolutions related to the cellular wireless network since its first trial was introduced in the 1970s. One of the inherent limitations of cellular networks is inter-cell interference which is the interference from other users in other cells. In particular, users at the cell boundaries perform badly due to the strong inter-cell interference which limits the performance of the whole networks. To reduce this bottleneck, network multiple-input multiple-output (MIMO) was introduced in the 2000s. In network MIMO, the base stations cooperate to serve the users. More precisely, the coverage area is divided into several disjoint clusters, each is jointly served by several base stations. Basically, network MIMO is equivalent to the cellular network with larger cell size and each cell is served by multiple base stations. There are still concepts of cells and cell boundaries, and hence, the inter-cell interference persists. In addition, network MIMO requires complicated signal co-processing with high backhaul overhead and deployment costs to reduce the effect of inter-cell interference.In this project, we are targeting a new practical, useful, and scalable version of network MIMO called "cell-free massive MIMO". In cell-free Massive MIMO, a number of access points, which are distributed at random in a very wide area (e.g. over an entire city), serve simultaneously many users randomly distributed in the same area. There are no concepts of cells or cell boundaries. Cell-free massive MIMO reaps all benefits obtained from massive MIMO and network MIMO, and hence, it is expected to offer many advantages compared with the conventional wireless systems: 1) huge data throughput; 2) huge energy efficiency; 3) and high coverage probability. Thus, cell-free Massive MIMO is a disruptive technology for next generations of densified wireless systems. Since cell-free massive MIMO a very new research topic, a number of issues and questions still need to be tackled before rolling-out it into practice. The main objective of this project is to develop a complete, useful, and practical cell-free massive MIMO system which includes signal processing schemes, channel estimation, pilot assignment schemes, power controls, and AP selection schemes. The application of the project results will contribute to the reduction of the ICT sector's contribution to global warming, through reduced power consumption and improved energy efficiency. It will also influence many dynamic economic sectors within the UK: telecom equipment manufacturing, telecom operators, smart cities, e-health, surveillance sector, military equipment and automotive companies.

对无线流量(数据流量和连接的设备数量)的需求呈指数级增长。随着无线设备(如智能手机、平板电脑和笔记本电脑)和服务/应用程序(如实时视频通话、高质量电影、实时3D游戏和物联网)的急剧增长，无线流量需求将继续增长。根据思科的数据，到2021年，全球移动数据流量将达到每月43艾字节，比2016年增长约7倍，比2018年增长3倍。到2021年，移动互联设备将达到116亿台，相当于人均1.5台。此外，人们越来越关注绿色通信(低能量辐射/低消耗)、安全和隐私。总而言之，未来的无线网络必须满足以下要求：(1)同时管理多个(数千甚至数百万)设备；(2)每个设备都需要高吞吐量(频谱效率)来支持多种服务/应用；(3)高能量效率；(4)高安全服务。移动网络是无线通信的核心网络之一。在传统的移动网络中，覆盖区域被划分为小区。每个小区由一个基站提供服务。自20世纪70年代引入第一次试验以来，我们已经看到了与蜂窝无线网络相关的许多革命。蜂窝网络固有的局限性之一是小区间干扰，即来自其他小区内其他用户的干扰。特别是，由于强烈的小区间干扰限制了整个网络的性能，在小区边界处的用户表现很差。为了减少这一瓶颈，网络多输入多输出(MIMO)在本世纪头十年被引入。在网络MIMO中，基站之间相互协作为用户提供服务。更准确地说，覆盖区域被划分为几个不相交的簇，每个簇由几个基站联合服务。网络MIMO基本上相当于小区规模较大的蜂窝网络，每个小区由多个基站服务。仍然存在小区和小区边界的概念，因此，小区间干扰仍然存在。此外，网络MIMO需要复杂的信号协同处理，具有较高的回程开销和部署成本，以减少小区间干扰的影响。在本项目中，我们的目标是一种新的实用、有用和可扩展的网络MIMO版本，称为无小区大规模MIMO。在无蜂窝大规模MIMO中，随机分布在非常广泛的区域(例如，整个城市)的多个接入点同时服务于在同一区域随机分布的多个用户。没有单元格或单元格边界的概念。无蜂窝海量MIMO充分利用了海量MIMO和网络MIMO的优点，因此与传统无线系统相比，它有望提供许多优势：1)巨大的数据吞吐量；2)巨大的能量效率；3)高覆盖概率。因此，无蜂窝大规模MIMO是下一代密集无线系统的颠覆性技术。由于无蜂窝大规模MIMO是一个非常新的研究课题，在将其推向实践之前，仍有许多问题和问题需要解决。该项目的主要目标是开发一个完整的、有用的、实用的大规模MIMO系统，包括信号处理方案、信道估计、导频分配方案、功率控制和AP选择方案。项目成果的应用将通过减少电力消耗和提高能源效率，有助于减少信息和通信技术部门对全球变暖的贡献。它还将影响英国国内许多充满活力的经济部门：电信设备制造、电信运营商、智慧城市、电子健康、监控部门、军事设备和汽车公司。

项目成果

Deep Learning-Aided Finite-Capacity Fronthaul Cell-Free Massive MIMO with Zero Forcing

• DOI: 10.1109/icc40277.2020.9149210
• 发表时间: 2020-06
• 期刊: ICC 2020 - 2020 IEEE International Conference on Communications (ICC)
• 作者: M. Bashar;A. Akbari;K. Cumanan;H. Ngo;A. Burr;P. Xiao;M. Debbah

Massive MIMO under Double Scattering Channels: Power Minimization and Congestion Controls

• DOI: 10.1109/icc42927.2021.9500981
• 发表时间: 2021-02
• 期刊: ICC 2021 - IEEE International Conference on Communications
• 作者: Trinh Van Chien;H. Ngo;S. Chatzinotas;B. Ottersten;M. Debbah

On the Energy Efficiency of Limited-Backhaul Cell-Free Massive MIMO

有限回程无小区大规模 MIMO 的能量效率

• DOI: 10.1109/icc.2019.8761134
• 发表时间: 2019
• 作者: Bashar M

On the Performance of Cell-Free Massive MIMO Relying on Adaptive NOMA/OMA Mode-Switching

• DOI: 10.1109/tcomm.2019.2952574
• 发表时间: 2020-02
• 期刊: IEEE Transactions on Communications
• 影响因子: 8.3
• 作者: M. Bashar;K. Cumanan;A. Burr;H. Ngo;L. Hanzo;P. Xiao

Uplink Spectral and Energy Efficiency of Cell-Free Massive MIMO With Optimal Uniform Quantization

• DOI: 10.1109/tcomm.2020.3028305
• 发表时间: 2021-01
• 期刊: IEEE Transactions on Communications
• 影响因子: 8.3
• 作者: M. Bashar;H. Ngo;K. Cumanan;A. Burr;P. Xiao;Emil Björnson;E. Larsson