Low complexity large scale MIMO processing

低复杂度大规模 MIMO 处理

• 批准号: 508260-2016
• 负责人: Damen, MohamedOussama
• 金额: $ 4.73万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=648592
• 关键词: Low; complexity; large; scale; MIMO

Massive multiple-input multiple-output (MIMO) systems, or large scale MIMO, are multiuser multiple antenna technologies that constitute one of the front runners proposed in the recent literature for solving the impending wireless network crunch that will result from the ever increasing number of subscribers and their data-hungry applications envisioned for the Internet of Things and 5G systems. In this proposal, we will tackle the problem of designing low complexity signal processing algorithms at both ends of large-scale MIMO transmission and reception. We will use our experience in designing efficient decoding algorithms for MIMO systems at a small-to-medium scale and exploit the nature of the massive MIMO in order to propose novel techniques taking advantages of the new channel characteristics, i.e., channel matrix sparsity and channel hardening around its mean value, while maintaining efficient signal processing algorithms. The system complexity will be distributed between the base stations, which can afford more complex algorithms, and the end-user terminals with low complexity processing constraints. At the base stations, we will consider the design of hybrid analog and digital beamforming algorithms with limited feedback on channel state information in order to decrease the number of costly radio frequency chains and improve the system efficiency. Then, we will consider the design of multiuser scheduling algorithms that take advantage of the sparse channel matrix for efficiently reducing it by blocks of manageable sizes. The design of training sequences required for beamforming and scheduling will also be investigated and analyzed in depth. Finally, we will tackle the problem of designing distributed massive MIMO systems, with practical considerations such as real-time processing, estimation errors, synchronization and interference management. Research and development on efficient transceivers designs targeting next generation wireless communications standards will have important commercial benefits to the Canadian IT sector, and this proposal will lead to the formation of two HQP who will gain both theoretical and practical skills in one of the most important and fast growing sectors of the Canadian economy.********************

大规模多输入多输出 (MIMO) 系统或大规模 MIMO 是多用户多天线技术，是最近文献中提出的领先技术之一，用于解决因物联网和 5G 系统设想的用户数量不断增加及其数据密集型应用而导致的即将到来的无线网络危机。在本提案中，我们将解决在大规模 MIMO 传输和接收两端设计低复杂度信号处理算法的问题。 我们将利用我们在中小型规模的 MIMO 系统设计高效解码算法方面的经验，并利用大规模 MIMO 的本质，提出利用新的信道特性（即信道矩阵稀疏性和围绕其平均值的信道强化）的新技术，同时保持高效的信号处理算法。系统复杂性将分布在能够承受更复杂算法的基站和具有低复杂性处理约束的最终用户终端之间。在基站，我们将考虑设计混合模拟和数字波束成形算法，对信道状态信息进行有限反馈，以减少昂贵的射频链数量并提高系统效率。然后，我们将考虑多用户调度算法的设计，该算法利用稀疏信道矩阵，通过可管理大小的块有效地减少它。波束成形和调度所需的训练序列的设计也将被深入研究和分析。最后，我们将解决设计分布式大规模 MIMO 系统的问题，并考虑实时处理、估计误差、同步和干扰管理等实际问题。针对下一代无线通信标准的高效收发器设计的研究和开发将为加拿大 IT 行业带来重要的商业利益，该提案将导致成立两个 HQP，他们将在加拿大经济最重要和快速增长的行业之一获得理论和实践技能。********************