商品描述
The authors explore various Unmanned Aerial Vehicle (UAV)-assisted massive Multiple-Input and Multiple-Output (MIMO) relaying systems designed for 5G-and-Beyond wireless networks. This book also addresses scenarios where a direct connection between a base station and users is blocked, and a UAV acts as a relay to ensure seamless connectivity. The goal is to maximize the total achievable rate by solving key optimization problems in UAV placement, power allocation, and beamforming design. To tackle these challenges, the authors present novel artificial intelligence (AI)-driven solutions that achieve near-optimal performance in complex environments. The first part introduces particle swarm optimization (PSO), a nature-inspired algorithm, for both single-user and multi-user massive MIMO settings, extending to multiple-UAV relay configurations. Our results demonstrate that PSO-based approaches can effectively enhance network capacity and coverage. The second part focuses on reducing computational complexity, while maintaining high performance. The authors develop deep learning (DL)-based approaches, from supervised learning for UAV placement and power allocation to deep reinforcement learning for trajectory optimization in dynamic conditions. Numerical evaluations confirm that these DL-based methods achieve reduced runtime without sacrificing achievable rates. This book targets researchers, advanced-level students and engineers interested in the challenges and practical solutions for UAV-assisted MIMO communications in wireless networks. Professionals working in wireless communications focused on this topic will also want to purchase this book.
商品描述(中文翻譯)
作者探討了各種無人機（UAV）輔助的大規模多輸入多輸出（MIMO）中繼系統，這些系統是為了5G及未來無線網絡而設計的。本書還針對基站與用戶之間的直接連接被阻塞的情況進行討論，無人機作為中繼以確保無縫連接。目標是通過解決無人機佈局、功率分配和波束成形設計中的關鍵優化問題來最大化總可達速率。為了應對這些挑戰，作者提出了新穎的人工智慧（AI）驅動解決方案，能在複雜環境中實現接近最佳的性能。
第一部分介紹了粒子群優化（PSO），這是一種受自然啟發的算法，適用於單用戶和多用戶的大規模MIMO設置，並擴展到多無人機中繼配置。我們的結果顯示，基於PSO的方法能有效提升網絡容量和覆蓋範圍。第二部分則專注於降低計算複雜度，同時保持高性能。作者開發了基於深度學習（DL）的方法，從無人機佈局和功率分配的監督學習到動態條件下的軌跡優化的深度強化學習。數值評估證實，這些基於深度學習的方法在不犧牲可達速率的情況下實現了運行時間的減少。
本書的目標讀者是對無人機輔助MIMO通訊在無線網絡中的挑戰和實用解決方案感興趣的研究人員、高級學生和工程師。專注於此主題的無線通訊專業人士也會希望購買本書。
作者簡介
Tho Le-Ngoc received the B.Eng. degree in electrical engineering and the M.Eng. degree in microprocessor applications from McGill University, Montreal, QC, Canada, in 1976 and 1978, respectively, and the Ph.D. degree in digital communications from the University of Ottawa, Ottawa, ON, Canada, in 1983. From 1977 to 1982, he was with Spar Aerospace Ltd., Sainte-Anne-de-Bellevue, QC, Canada, involved in the development and design of satellite communications systems. From 1982 to 1985, he was with SRTelecom, Inc., Saint Laurent, QC, Canada, where he developed the new point-to-multipoint DA-TDMA/TDM Subscriber Radio System SR500. From 1985 to 2000, he was a Professor with the Department of Electrical and Computer Engineering, Concordia University, Montreal. Since 2000, he has been with the Department of Electrical and Computer Engineering, McGill University. His research interest includes broadband digital communications. Dr. Le-Ngoc was a recipient of the 2004 Canadian Award in Telecommunications Research and the IEEE Canada Fessenden Award in 2005. He is a Distinguished James McGill Professor, and a Fellow of the Engineering Institute of Canada, the Canadian Academy of Engineering, and the Royal Society of Canada. Mohammadmahdi Ghadaksaz received the B.Sc. (Hons.) degree in electrical engineering from the Amirkabir University of Technology, Tehran, Iran, in 2023, the M.Sc. degree in electrical and computer engineering from the McGill University, Montreal, QC, in 2025. He is the recipient of McGill Graduate Excellence Fellowship, and the member of National Elite Foundation of Iran. His main research interests include reinforcement learning, deep learning, signal processing, wireless communication, and communication networks. Mobeen Mahmood received his B.Sc. (Hons.) in Electrical Engineering from the University of Engineering and Technology (UET), Taxila, Pakistan in 2013, M.Sc. (Hons.) Electrical Engineering from the American University of Sharjah (AUS), Sharjah, UAE in 2019, and Ph.D. in Electrical Engineering from McGill University, Montreal, QC, Canada in 2024. From 2014 to 2017, he was with China Mobile Pakistan (CMPak), Islamabad, Pakistan. He is the recipient of AUS teaching assistantship, AUS research assistantship, Fonds de Recherche du Québec-Nature and Technologies (FRQNT), IEEE VTS Student Travel Award, IEEE Canada Vehicular Technologies Grant, McGill Graduate Research Enhancement and Travel Award (GREAT Award), McGill Graduate Excellence Fellowship, McGill Engineering Class of 1936 Fellowship and J.W.McConnell Memorial Fellowship as part of McGill Engineering Doctoral Award (MEDA). His main research interests include massive MIMO, hybrid beamforming, UAV communications, AI-enable wireless networks, and full-duplex communications.
作者簡介(中文翻譯)
Tho Le-Ngoc 於1976年和1978年分別在加拿大蒙特利爾的麥吉爾大學獲得電機工程學士學位（B.Eng.）和微處理器應用碩士學位（M.Eng.），並於1983年在加拿大渥太華的渥太華大學獲得數位通訊博士學位（Ph.D.）。從1977年到1982年，他在加拿大聖安娜德貝爾維尤的Spar Aerospace Ltd.工作，參與衛星通訊系統的開發和設計。從1982年到1985年，他在加拿大聖洛朗的SRTelecom, Inc.工作，開發了新的點對多點DA-TDMA/TDM用戶無線電系統SR500。從1985年到2000年，他擔任蒙特利爾康考迪亞大學電機與計算機工程系的教授。自2000年以來，他一直在麥吉爾大學電機與計算機工程系任教。他的研究興趣包括寬頻數位通訊。Le-Ngoc博士曾獲得2004年加拿大電信研究獎和2005年IEEE加拿大Fessenden獎。他是傑出的James McGill教授，也是加拿大工程學會、加拿大工程院和加拿大皇家學會的院士。
Mohammadmahdi Ghadaksaz 於2023年在伊朗德黑蘭的阿米爾卡比爾科技大學獲得電機工程榮譽學士學位（B.Sc. (Hons.)），並於2025年在加拿大蒙特利爾的麥吉爾大學獲得電機與計算機工程碩士學位（M.Sc.）。他是麥吉爾大學研究生卓越獎學金的獲得者，也是伊朗國家精英基金會的成員。他的主要研究興趣包括強化學習、深度學習、信號處理、無線通訊和通訊網路。
Mobeen Mahmood 於2013年在巴基斯坦塔克西拉的工程與技術大學（UET）獲得電機工程榮譽學士學位（B.Sc. (Hons.)），於2019年在阿聯酋沙迦的沙迦美國大學（AUS）獲得電機工程榮譽碩士學位（M.Sc. (Hons.)），並於2024年在加拿大蒙特利爾的麥吉爾大學獲得電機工程博士學位（Ph.D.）。從2014年到2017年，他在巴基斯坦伊斯蘭堡的中國移動巴基斯坦（CMPak）工作。他獲得了AUS教學助理獎學金、AUS研究助理獎學金、魁北克自然與技術研究基金（FRQNT）、IEEE VTS學生旅行獎、IEEE加拿大車輛技術獎學金、麥吉爾大學研究生研究增強與旅行獎（GREAT Award）、麥吉爾大學研究生卓越獎學金、麥吉爾工程1936班獎學金和J.W. McConnell紀念獎學金，這些都是麥吉爾工程博士獎（MEDA）的一部分。他的主要研究興趣包括大規模MIMO、混合波束成形、無人機通訊、AI驅動的無線網路和全雙工通訊。
