4G Femtocells: Resource Allocation and Interference Management (SpringerBriefs in Computer Science) - Softcover

Zhang, Haijun

Softcover

ISBN 10: 1461490790 ISBN 13: 9781461490791

Verlag: Springer, 2013

Inhaltsangabe

This brief examines resource allocation and interference management for 4G femtocells. It introduces 4G femtocells in the context of 4G mobile networks and discusses related technical challenges in resource allocation and interference management. Topics include ant colony algorithm based downlink resource allocation, intelligent scheduling and power control, uplink and downlink for two-tier networks, quality of service (QoS) constraints and the cross-tier interference constraint. The authors present algorithms to alleviate common femtocell-related problems such as subchannel power allocation. The complexity of the proposed resource allocation algorithms is analyzed, and the effectiveness of the proposed algorithms is verified by simulations. This concise and practical book directly addresses common problems relating to femtocells and resource management. It serves as a useful tool for researchers in the field. Advanced-level students or professionals interested in femtocells and networks will also find the content helpful.

Über diesen Titel

Über die Autorin bzw. den Autor

Haijun Zhang (Fellow, IEEE) is currently a Full Professor and Dean at University of Science and Technology Beijing, China. He was a Postdoctoral Research Fellow in Department of Electrical and Computer Engineering, the University of British Columbia (UBC), Canada. He serves/served as Track Co-Chair of VTC Fall 2022 and WCNC 2020/2021, Symposium Chair of Globecom'19, TPC Co-Chair of INFOCOM 2018 Workshop on Integrating Edge Computing, Caching, and Offloading in Next Generation Networks, and General Co-Chair of GameNets'16. He serves as an Editor of IEEE Transactions on Wireless Communications, IEEE Transactions on Information Forensics and Security, and IEEE Transactions on Communications. He received the IEEE CSIM Technical Committee Best Journal Paper Award in 2018, IEEE ComSoc Young Author Best Paper Award in 2017, IEEE ComSoc Asia-Pacific Best Young Researcher Award in 2019. He is a Distinguished Lecturer of IEEE and IEEE Fellow. Ning Yang is an assistant researcher at the Institute of Automation, Chinese Academy of Sciences (CASIA). Her research areas include reinforcement learning and the application of reinforcement learning in combinatorial optimization. She received her Ph.D. from at University of Science and Technology Beijing in 2020, supervised by Prof. Haijun Zhang. Before joining CASIA, she was a visiting student working with Prof. Randall Berry from 2019 to 2020 at Electrical and Computer Engineering, Northwestern University. She received the Best Paper IEEE 87th Vehicular Technology Conference in 2018.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2013
• Sprache: Englisch
• ISBN 10: 1461490790
• ISBN 13: 9781461490791
• Einband: Taschenbuch
• Anzahl der Seiten: 88
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Deutschland