AI-Based transceivers for massive MIMO wireless communications
用于大规模 MIMO 无线通信的基于 AI 的收发器
基本信息
- 批准号:555846-2020
- 负责人:
- 金额:$ 2.68万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Alliance Grants
- 财政年份:2022
- 资助国家:加拿大
- 起止时间:2022-01-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Demands for throughput and latency improvements in 5G-and-beyond wireless networks continue to grow at an increasing pace, boosted by new multi-media and social network applications, and new types of massive connectivity such as machine-to-machine (M2M). To meet these growing demands, the use of massive multiple-input multiple-output (M-MIMO) systems operating in the mmWave and THz bands has been recently considered. However, the design of multi-user (MU) M-MIMO transceivers with large-scale antenna arrays (LSAAs) for optimal operation under complex radio conditions and user patterns poses formidable problems, seemingly intractable by traditional means. Artificial intelligence (AI) and machine learning (ML) have the potential to overcome this challenge by exploiting all possible side information relevant to intelligent transceiver signal processing and operations. This proposed 3-year research in collaboration with InterDigital Canada is aimed at studying and developing new AI-enabled transceiver design techniques and algorithms for MU-M-MIMO communications in sub-6GHz, mmWave and THz bands. Cutting-edge ML approaches, especially deep learning (DL) architectures that employ multiple hidden processing layers to learn complex non-linear relationships from large amount of data, will be a corner stone of our work. In recent years, InterDigital has taken a leading role in the development of new technologies for 5G wireless and, as part of this initiative, it will support our research activities through cash and in-kind contributions. AI-enabled MU-M-MIMO transceivers in sub-6GHz, mmWave and THz bands will bridge the performance gap between existing 4G technology and future 5G-and-beyond wireless networks. The proposed research is of great importance to InterDigital and Canada: it will empower the company with critical knowledge and expertise in the key area of AI-enabled wireless networking, and help our country maintain a strategic position in the development, standardization and commercialization of advanced information and communications technologies.
在新的多媒体和社交网络应用以及机器到机器(M2M)等新型海量连接的推动下,5G及以上无线网络对吞吐量和延迟改进的需求继续以越来越快的速度增长。为了满足这些不断增长的需求,最近考虑使用工作在毫米波和太赫兹频段的大规模多输入多输出(M-MIMO)系统。然而,具有大规模天线阵列(LSA)的多用户(MU)M-MIMO收发信机的设计在复杂的无线电条件和用户模式下的优化运行带来了巨大的问题,通过传统的方法似乎是难以解决的。人工智能(AI)和机器学习(ML)通过利用与智能收发信机信号处理和操作相关的所有可能的辅助信息,具有克服这一挑战的潜力。这项拟议的为期3年的研究与InterDigital Canada合作,旨在研究和开发用于低于6 GHz、毫米波和太赫兹频段的MU-M-MIMO通信的新的启用人工智能的收发器设计技术和算法。尖端的ML方法,特别是使用多个隐藏处理层从大量数据中学习复杂非线性关系的深度学习(DL)体系结构,将是我们工作的基石。近年来,InterDigital在5G无线新技术的开发中发挥了主导作用,作为这一倡议的一部分,它将通过现金和实物捐款支持我们的研究活动。支持人工智能的低于6 GHz、毫米波和太赫兹频段的MU-M-MIMO收发器将弥合现有4G技术和未来5G及以上无线网络之间的性能差距。拟议中的研究对InterDigital和加拿大非常重要:它将使公司在人工智能无线网络关键领域拥有关键知识和专业知识,并帮助我国在先进信息和通信技术的开发、标准化和商业化方面保持战略地位。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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LeNgoc, ThoT其他文献
LeNgoc, ThoT的其他文献
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{{ truncateString('LeNgoc, ThoT', 18)}}的其他基金
NSERC/Huawei Technologies Canada Industrial Research Chair in Dense Broadband Wireless Access Networks(dBwan)
NSERC/华为技术加拿大密集宽带无线接入网络(dBwan)工业研究主席
- 批准号:
366566-2018 - 财政年份:2022
- 资助金额:
$ 2.68万 - 项目类别:
Industrial Research Chairs
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