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: $ 1.78万
• 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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=618680
• 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.

大量的多输入多输出（MIMO）系统或大型MIMO是多源多个天线技术，构成了最近文献中提出的用于解决即将到来的无线网络紧缩的前跑者之一，这将源于越来越多订户及其渴望数据的应用程序设想为物联网和5G系统。在此提案中，我们将解决在大规模MIMO传播和接收的两端设计低复杂性信号处理算法的问题。我们将利用我们的经验在设计有效的MIMO系统的有效解码算法上，以小型到中等的比例并利用大型MIMO的性质，以提出具有新的通道特征的优势，即通道矩阵稀疏性和渠道的新技术围绕其平均值硬化，同时保持有效的信号处理算法。系统的复杂性将分布在基站之间，该基站可以提供更复杂的算法，而最终用户终端具有较低的复杂性处理约束。在基站，我们将考虑混合模拟和数字波束形成算法的设计，对通道状态信息的反馈有限，以减少昂贵的射频链的数量并提高系统效率。然后，我们将考虑使用稀疏通道矩阵的多源调度算法的设计，以通过可管理的尺寸块有效地减少它。还将深入研究和分析波束形成和调度所需的训练序列的设计。最后，我们将解决设计分布式大型MIMO系统的问题，并具有实时处理，估计错误，同步和干扰管理等实际考虑。针对下一代无线通信标准的有效收发器设计的研究和开发将对加拿大IT领域具有重要的商业利益，该提案将导致两个HQP的形成，他们将在最重要的和最重要的和最重要的和实用的技能中获得最重要的和实用技能加拿大经济的快速发展。