Yang / Chen / Liu Positioning and Sensing Over Wireless Networks

1. Auflage 2025
ISBN: 978-3-031-99162-2
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 181 Seiten

Reihe: Professional and Applied Computing (R0)

This book covers the principles, methods, and state-of-the-art applications of positioning and sensing across both ground-based and aerial wireless networks. The first two chapters introduce key performance metrics and measurement techniques along with enabling tools. In the next two chapters, this book examines radio-frequency implementations over Wi-Fi systems, followed by visible-light positioning systems.

Building on these chapters, fusion-based strategies demonstrate how inertial sensors, floor plans, and environmental constraints can be integrated via adaptive filter to enhance positioning accuracy. Subsequent chapters explore unmanned aerial vehicle–assisted positioning. Finally, this book presents integrated sensing–communication frameworks that design joint UAV Trajectory and resource allocations to deliver simultaneous connectivity and environmental awareness.

This book targets graduate-level students and researchers working in computer science and electrical engineering as well as industry engineers. It offers both theoretical foundations and practical guidelines to develop next-generation wireless networks and beyond positioning and sensing solutions.

Zielgruppe

Research

Autoren/Hrsg.

Yang, Yang

Chen, Mingzhe

Liu, Fan

Mao, Shiwen

Inhaltsverzeichnis

Chapter 1 Introduction.- 1.1 An Overview of Positioning and Sensing.- 1.1.1 Background.- 1.1.2 Motivation.- 1.2 Applications of Positioning and Sensing.- 1.2.1 Public Provision.- 1.2.2 Enterprise.- 1.2.3 Individuals.- 1.3 Organization of the Monograph.- Chapter 2 Key Performance Indicators and Measurements.- 2.1 KPIs.- 2.2 Measurement.- 2.2.1 Time-Based Measurements.- 2.2.2 Angle-Based Measurements.- 2.2.3 Received Signal Strength-Based Measurements.- 2.2.4 Others.- 2.3 Summary.- Chapter 3 Key Techniques for Positioning and Sensing.- 3.1 Machine Learning.- 3.1.1 Deep Neural Networks.- 3.1.2 Large Models.- 3.2 Adaptive System.- 3.2.1 Kalman Filter.- 3.2.2 Particle Filter.- 3.3 Reconfigurable Intelligent Surface.- 3.3.1 Active Reflectors.- 3.3.2 Passive Reflectors.- 3.4 Software Defined Network.- 3.5 Summary.- Chapter 4 Positioning and Sensing Over Radio Frequency Wireless Networks.- 4.1 Introduction.- 4.1.1 Background.- 4.1.2 Motivations.- 4.2 Models and Problem Formulation.- 4.2.1 System Model.- 4.2.2 Problem Formulation.- 4.3 State-of-the-art Progress.- 4.4 An Efficient RF-based Sensing Scheme.- 4.4.1 Scheme Construction.- 4.4.2 Performance Evaluation.- 4.5 Summary.- Chapter 5 Positioning and Sensing Over Optical Wireless Networks.- 5.1 Introduction.- 5.1.1 Background.- 5.1.2 Motivations.- 5.2 Models and Problem Formulation.- 5.2.1 System Model.- 5.2.2 Problem Formulation.- 5.3 State-of-the-art Progress.- 5.4 An Accurate Single-LED-based Visible Light Positioning Scheme.- 5.4.1 Scheme Construction.- 5.4.2 Performance Evaluation.- 5.5 Summary.- Chapter 6 Positioning and Sensing for UAVs.- 6.1 Introduction.- 6.1.1 Background.- 6.1.2 Motivations.- 6.2 Models and Problem formulation.- 6.2.1 System Model.- 6.2.2 Problem Formulation.- 6.3 Algorithm Design.- 6.4 Performance Evaluation.- 6.5 Summary.- Chapter 7 Conclusion and Future Works.- 7.1 Conclusion.- 7.2 Future Works.

Über Autor(innen)

Yang Yang received the B.S degree in information engineering from the School of Communication, Xidian University, Xi' an, China, in June 2013, and the Ph.D. degree in information and communication engineering from the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in June 2018. He is currently an Associate Professor with the School of Information and Communication Engineering BUPT. His research interests include intelligent wireless communications and positioning. He was a recipient of the IEEE WCNC 2021 Best Paper Award. He published more than 70 papers in high quality journals and conferences such as IEEE JSAC/TWC/GLOBECOM/ICC. He organized several symposium/workshops for IEEE GLOBECOM, IEEE ICC, IEEE WCNC and IEEE WCSP.

Mingzhe Chen is currently an Assistant Professor with the Department of Electrical and Computer Engineering and the Knight Foundation Chair in Data Science and AI in the Frost Institute of Data Science and Computing at University of Miami. His research interests include federated learning, reinforcement learning, virtual reality, unmanned aerial vehicles, and Internet of Things. He has received four IEEE Communication Society journal paper awards including the IEEE Marconi Prize Paper Award in Wireless Communications in 2023, the Young Author Best Paper Award in 2021 and 2023, and the Fred W. Ellersick Prize Award in 2022, and four conference best paper awards at ICCCN in 2023, IEEE WCNC in 2021, IEEE ICC in 2020, and IEEE GLOBECOM in 2020.

Prof. Liu's research interests lie in the general area of signal processing and wireless communications, and in particular in the area of Integrated Sensing and Communications (ISAC). He is the founding Academic Chair of the IEEE ComSoc ISAC Emerging Technology Initiative (ISAC-ETI), Vice Chair and founding member of the IEEE SPS ISAC Technical Working Group (ISAC-TWG), an elected member of the IEEE SPS Sensor Array and Multichannel Technical Committee (SAM-TC), an Associate Editor of the IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, and IEEE Open Journal of Signal Processing, and a Guest Editor of the IEEE Journal on Selected Areas in Communications, IEEE Wireless Communications, and IEEE Vehicular Technology Magazine. He was a TPC Co-Chair of the 2nd-4th IEEE Joint Communication and Sensing (JC&S) Symposium, a Symposium Co-Chair for IEEE ICC 2026 and IEEE GLOBECOM 2023, and a Track Co-Chair for the IEEE WCNC 2024. He is a member of the IMT-2030 (6G) ISAC Task Group. He was listed among the World's Top 2% Scientists by Stanford University for citation impact from 2021 to 2024, and among the 2023 Elsevier Highly-Cited Chinese Researchers. He was a recipient of numerous Best Paper Awards, including the 2024 IEEE SPS Best Paper Award, 2024 IEEE SPS Donald G. Fink Overview Paper Award, 2024 IEEE ComSoc Asia-Pacific Outstanding Paper Award, 2023 IEEE Communications Society Stephan O. Rice Prize, and 2021 IEEE SPS Young Author Best Paper Award. He is a Senior Member of the IEEE.

Shiwen Mao is a Professor and Earle C. Williams Eminent Scholar, and Director of the Wireless Engineering Research and Education Center at Auburn University. Dr. Mao's research interest includes wireless networks, multimedia communications, and smart grid. He is a Distinguished Lecturer of IEEE Communications Society and IEEE Council of RFID, and the editor-in-chief of IEEE Transactions on Cognitive Communications and Networking. He received the IEEE ComSoc MMTC Outstanding Researcher Award in 2023, the SEC (Southeastern Conference) 2023 Faculty Achievement Award for Auburn, the IEEE ComSoc TC-CSR Distinguished Technical Achievement Award in 2019, the Auburn University Creative Research & Scholarship Award in 2018, the NSF CAREER Award in 2010, and several service awards from the IEEE. He is a co-recipient of several journal and conference best paper/demo awards from the IEEE.