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Efficient Integration of 5G and Beyond Heterogeneous Networks

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Efficient Integration of 5G and Beyond Heterogeneous Networks/ by Zi-Yang Wu, Muhammad Ismail, Justin Kong, Erchin Serpedin, Jiao Wang.
作者:	Wu, Zi-Yang.
其他作者:	Ismail, Muhammad.
面頁冊數:	XII, 124 p. 38 illus., 31 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computer organization. -
電子資源:	https://doi.org/10.1007/978-981-15-6938-8
ISBN:	9789811569388

Efficient Integration of 5G and Beyond Heterogeneous Networks
Wu, Zi-Yang.

Efficient Integration of 5G and Beyond Heterogeneous Networks[electronic resource] /by Zi-Yang Wu, Muhammad Ismail, Justin Kong, Erchin Serpedin, Jiao Wang. - 1st ed. 2020. - XII, 124 p. 38 illus., 31 illus. in color.online resource.

Chapter 1. Introduction -- Chapter 2. Efficient Joint Planning of HetNets -- Chapter 3. Realization of Mobile Indoor Channels -- Chapter 4. Data-driven Handover Algorithm in Mobile HetNets -- Chapter 5. Data-driven Multi-homing Resource Allocation in Mobile HetNets -- Chapter 6. Conclusions.

This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects. The integration of high-frequency air interfaces into 5G+ wireless networks can relieve the congested radio frequency (RF) bands. Visible light communication (VLC) is now emerging as a promising candidate for future generations of HetNets. Heterogeneous RF-optical networks combine the high throughput of visible light and the high reliability of RF. However, when implementing these HetNets in mobile scenarios, several challenges arise from both planning and operational perspectives. Since the mmWave, terahertz, and visible light bands share similar wave propagation characteristics, the concepts presented here can be broadly applied in all such bands. To facilitate the planning of RF-optical HetNets, the authors present an algorithm that specifies the joint optimal densities of the base stations by drawing on stochastic geometry in order to satisfy the users’ quality-of-service (QoS) demands with minimum network power consumption. From an operational perspective, the book explores vertical handovers and multi-homing using a cooperative framework. For vertical handovers, it employs a data-driven approach based on deep neural networks to predict abrupt optical outages; and, on the basis of this prediction, proposes a reinforcement learning strategy that ensures minimal network latency during handovers. In terms of multi-homing support, the authors examine the aggregation of the resources from both optical and RF networks, adopting a two-timescale multi-agent reinforcement learning strategy for optimal power allocation. Presenting comprehensive planning and operational strategies, the book allows readers to gain an in-depth grasp of how to integrate future coexisting networks at high-frequency bands in a cooperative manner, yielding reliable and high-speed 5G+ HetNets.

ISBN: 9789811569388

Standard No.: 10.1007/978-981-15-6938-8doiSubjects--Topical Terms:

596298
Computer organization.

LC Class. No.: QA76.9.C643

Dewey Class. No.: 004.6

Efficient Integration of 5G and Beyond Heterogeneous Networks
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