Signal Prosessing Techniques for 5G Wireless and mm-Wave Communications

5G 无线和毫米波通信的信号处理技术

• 批准号: RGPIN-2017-04223
• 负责人: Champagne, Benoit
• 金额: $ 3.42万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689575
• 关键词: Signal; Prosessing; Techniques; 5G; Wireless

Extraordinary advances in wireless network technology during the past decade have revolutionized the way in which we use personal communications. As a result of such benefits, the user demand for throughput continues to grow at a stunning rate of 50% annually. Anticipating that current 4th generation (4G) of wireless systems will not meet the demand for future services, standardization bodies have set forth impressive target specifications for the 5th generation (5G), with multi-fold enhancements in data rate, connectivity, energy efficiency, and quality of service (QoS). Reaching such high-end performance in a spectrum congested environment calls for the introduction of new physical layer technologies along with sophisticated signal processing algorithms.*******The long-term goal of the proposed research is to develop and investigate new signal processing concepts, theories and algorithms, to meet the demands of emerging 5G mobile networks and beyond. Key innovative aspects include a focus on location-aware information processing, which provides the unifying theme for the proposed work, along with an emphasis on the use of multi-antenna systems operated in higher frequency bands, i.e. shift towards mm-waves. Within this exacting framework, the short-term objectives of the program are articulated around three complementary topics, namely: (1) modulation formats and waveform design; (2) space-time processing for large-scale antenna arrays; and (3) device localization in ultra-dense networks. Under the first topic, we will study new adaptive multi-carrier modulation (MCM) techniques that take advantage of location-based information to optimize spectrum efficiency over time, across the network. These new schemes will then be extended for application to massive multiple-input multiple-output (MIMO) transceiver configurations. Under the second topic, we will develop improved algorithms for the estimation of location-based parameters, including: direction of arrival (DoA) and time of arrival (ToA). We will also investigate new low-complexity 3D beamforming algorithms, with a focus on beamspace methods. Under the third topic, we will research novel on-line algorithms for the localization and tracking of mobile devices using both line-of-sight (LoS) and non-LOS (NLoS) measurements. Finally, these algorithms will be generalized to distributed forms of processing, for practical application in dense heterogeneous networks.*******This program of research will provide numerous opportunities for HQP training at the M.Eng. and Ph.D. levels, while the main findings will be presented at international conferences and published in highly selective journals.***

在过去的十年中，无线网络技术的非凡进步彻底改变了我们使用个人通信的方式。由于这些好处，用户对吞吐量的需求继续以每年50%的惊人速度增长。预计当前的第四代（4G）无线系统将无法满足未来服务的需求，标准化机构已经为第五代（5G）提出了令人印象深刻的目标规范，在数据速率、连接性、能效和服务质量（QoS）方面有多方面的增强。要在频谱拥挤的环境中达到如此高端的性能，需要引入新的物理层技术，沿着引入复杂的信号处理算法。*拟议研究的长期目标是开发和研究新的信号处理概念、理论和算法，以满足新兴的5G移动的网络及其他网络的需求。关键的创新方面包括对位置感知信息处理的关注，这为拟议的工作提供了统一的主题，沿着强调使用在更高频段工作的多天线系统，即向毫米波转移。在这个严格的框架内，该计划的短期目标围绕三个互补的主题进行阐述，即：（1）调制格式和波形设计;（2）大规模天线阵列的时空处理;（3）超密集网络中的设备定位。在第一个主题下，我们将研究新的自适应多载波调制（MCM）技术，该技术利用基于位置的信息来优化整个网络的频谱效率。这些新的计划，然后将扩展应用到大规模的多输入多输出（MIMO）收发器配置。在第二个主题下，我们将开发改进的算法来估计基于位置的参数，包括：到达方向（DoA）和到达时间（ToA）。我们还将研究新的低复杂度3D波束形成算法，重点是波束空间方法。在第三个主题下，我们将研究新的在线算法的定位和跟踪的移动的设备使用的视线（LoS）和非视线（NLoS）的测量。最后，这些算法将被推广到分布式处理形式，以便在密集异构网络中得到实际应用。该研究计划将为工程硕士和博士的HQP培训提供许多机会。主要研究结果将在国际会议上提出，并在高度精选的期刊上发表。