Massive MIMO wireless networks: Theory and methods

频谱是一种宝贵但稀缺的自然资源。在英国，Ofcom将腾出800 MHz的模拟电视频谱(连同可用的2.6 GHz频段)用于4G，这已经为国家财政筹集了23.4亿GB。根据英国通信办公室的数据，英国人每月在移动中消费的数据量已经达到2000万GB，这主要是因为用户在移动中参与了视频、电视和电影。移动运营商的共识也是，到2020年，需要将系统容量增加1000倍，以避免移动网络陷入停顿。因此，最大化频谱效率是一个主要问题，而频谱效率受到包括4G在内的无线网络的干扰和衰落的限制。阿尔卡特-朗讯倡导的一个新兴想法是大规模MIMO天线系统，它已经得到了供应商和运营商的认真考虑。这项技术有可能解决频谱稀缺的问题，并通过允许数十个或数百个终端在相同的时频资源中同时接入，极大地提高频谱利用率。为了使大规模MIMO技术最大限度地发挥其潜力，需要解决由于导频污染、信号功率的快速时空变化和自主资源分配而导致的信道估计和捕获方面的各种挑战，特别是在存在大量用户同时接入的情况下。这个项目的重点是通过推进信息论、估计论和网络优化的各个方面来应对这些根本的挑战。特别是，我们将在以下方面做出贡献：对非均匀相关结构支撑的海量MIMO信道进行建模；根据随机矩阵理论通过收缩估计器进行信息论分析；在存在信道估计误差的情况下针对海量MIMO进行稳健的预编码器设计；在存在严重导频污染的情况下发展新的信道估计技术；以及提出和分析用于自主资源分配和导频分配的博弈论算法。所有开发的概念和算法将被整合，并将使用基于LTE-Advanced标准及其向5G的演进的模拟参考系统来评估无线电链路层性能。工业伙伴将参与整个项目，以确保我们的工作与工业相关。

Spectrum is a precious but scarce natural resource. In the UK, Ofcom will free up the analogue TV spectrum at 800MHz (together with the available 2.6GHz band) for 4G, which has already raised £2.34 billion for the national purse. According to Ofcom, the amount of data Britons consume on the move each month has already hit 20 million gigabytes, mainly due to users' engagement of video, TV and films while on the move. It is also a common understanding for the mobile operators that by 2020 a 1000 times increase in the system capacity will be needed to avoid mobile networks grinding to a halt. Maximising spectral efficiency, which is limited by interference and fading for wireless networks including 4G, is therefore a major issue. An emerging idea, which is championed by Alcatel-Lucent and has already received serious consideration by vendors and operators is that of a massive MIMO antenna system. This technology has the potential to unlock the issue of spectrum scarcity and to enhance spectrum usage tremendously by enabling simultaneous access of tens or hundreds of terminals in the same time-frequency resource. In order for massive MIMO technology to attain its utmost potential, it is important that various challenges in terms of channel estimation and acquisition due to pilot contamination, fast spatial-temporal variations in signal power and autonomous resource allocation, in particular in the presence of simultaneous access of a large number of users need to be addressed. The focus of this project is on tackling these fundamental challenges, by advancing aspects of information theory, estimation theory and network optimisations. In particular, we will contribute in terms of modelling massive MIMO channels underpinned by heterogeneous correlation structures; performing information theoretic analysis in terms of random matrix theory through shrinkage estimators; robust precoder design for massive MIMO in the presence of channel estimation errors; developing novel channel estimation technique in the presence of severe pilot contamination; and proposing and analysing game theoretic algorithms for autonomous resource allocation and pilot assignments. All the concepts and algorithms developed will be integrated and the radio link layer performance will be assessed using a simulation reference system based on LTE-Advanced standards and its evolution towards 5G. Industrial partners will be engaged throughout the project to ensure industrial relevance of our work.