Cognitive Radio Networks: Efficient Resource Allocation in Cooperative Sensing, Cellular Communications, High-Speed Vehicles, and Smart Grid

Cognitive Radio Networks: Efficient Resource Allocation in Cooperative Sensing, Cellular Communications, High-Speed Vehicles, and Smart Grid

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Overview

Cognitive Radio Networks: Efficient Resource Allocation in Cooperative Sensing, Cellular Communications, High-Speed Vehicles, and Smart Grid by Tao Jiang, Zhiqiang Wang, Yang Cao, Zhijiang Zhang

Resource allocation is an important issue in wireless communication networks. In recent decades, cognitive radio-based networks have garnered increased attention and have been well studied to overcome the problem of spectrum scarcity in future wireless communications systems. Many new challenges in resource allocation appear in cognitive radio-based networks. This book focuses on effective resource allocation solutions in several important cognitive radio-based networks, including opportunistic spectrum access networks, cooperative sensing networks, cellular networks, high-speed vehicle networks, and smart grids.

Cognitive radio networks are composed of cognitive, spectrum-agile devices capable of changing their configuration on the fly based on the spectral environment. This capability makes it possible to design flexible and dynamic spectrum access strategies with the purpose of opportunistically reusing portions of the spectrum temporarily vacated by licensed primary users. Different cognitive radio-based networks focus on different network resources, such as transmission slots, sensing nodes, transmission power, white space, and sensing channels.

This book introduces several innovative resource allocation schemes for different cognitive radio-based networks according to their network characteristics:


  • Opportunistic spectrum access networks – Introduces a probabilistic slot allocation scheme to effectively allocate the transmission slots to secondary users to maximize throughput
  • Cooperative sensing networks – Introduces a new adaptive collaboration sensing scheme in which the resources of secondary users are effectively utilized to sense the channels for efficient acquisition of spectrum opportunities
  • Cellular networks – Introduces a framework of cognitive radio-assisted cooperation for downlink transmissions to allocate transmission modes, relay stations, and transmission power/sub-channels to secondary users to maximize throughput
  • High-speed vehicle networks – Introduces schemes to maximize the utilized TV white space through effective allocation of white space resources to secondary users
  • Smart grids – Introduces effective sensing channel allocation strategies for acquiring enough available spectrum channels for communications between utility and electricity consumers

Product Details

ISBN-13: 9781498721134
Publisher: Taylor & Francis
Publication date: 04/08/2015
Pages: 148
Product dimensions: 6.40(w) x 9.30(h) x 0.60(d)

About the Author

Tao Jiang is currently a chair professor in the School of Electronics Information and Communications, Huazhong University of Science and Technology, Wuhan, P. R. China (PRC). He received the Ph.D. degree in information and communication engineering from Huazhong University of Science and Technology, Wuhan, PRC in April 2004. He has authored or co-authored over 200 technical papers in major journals and conferences and six books/chapters in the areas of communications and networks. He served or is serving as associate editor of some technical journals in communications, including IEEE Transactions on Signal Processing, IEEE Communications Surveys and Tutorials, IEEE Transactions on Vehicular Technology, and IEEE Internet of Things Journal. He is a recipient of the NSFC for Distinguished Young Scholars Award in PRC.

Zhiqiang Wang currently works at State Grid Shaanxi Electric Power Company Telematics. He received a B.S. from Xian Jiaotong University, Xian, PRC in 2006, and M.S. and Ph.D. degrees from Huazhong University of Science and Technology, Wuhan, PRC in 2009 and 2012, respectively. Wang’s current research interests include the areas of energy management and smart grid communications.

Yang Cao is currently an assistant professor in School of Electronics Information and Communications, Huazhong University of Science and Technology, Wuhan, PRC. He received Ph.D. and B.S. degrees in information and communications engineering at Huazhong University of Science and Technology, Wuhan, PRC in 2014 and 2009, respectively. His research interests include resource allocation for cellular device-to-device communications and smart grids.

Table of Contents

Preface
Acknowledgments
About the Authors

Introduction
Cognitive Radio-Based Networks
Opportunistic Spectrum Access Networks
Cognitive Radio Networks with Cooperative Sensing
Cognitive Radio Networks for Cellular Communications
Cognitive Radio Networks for High-Speed Vehicles
Cognitive Radio Networks for a Smart Grid
Content and Organization

Transmission Slot Allocation in an Opportunistic Spectrum Access Network
Single-User Single-Channel System Model
Probabilistic Slot Allocation Scheme
Optimal Probabilistic Slot Allocation
Baseline Performance
Exponential Distribution
Hyper-Erlang Distribution

Performance Analysis and Evaluation
Impact of Sensing Errors
Impact of Unknown Primary User Idle Period Distribution
Performance Comparisons

Summary

Sensing Node Allocation in a Cognitive Radio Network with Cooperative Sensing
Multi-User Multi-Channel System Model
Adaptive Collaboration Sensing Scheme
Basic Idea
Sequential Probability Ratio Test
Optimal Sensing Node Allocation

Performance Evaluation and Analysis
Summary

Transmission Power Allocation in a Cognitive Radio Network
Cognitive Radio-Assisted Cooperation Framework
Optimal Transmission Power Allocation
Cross-Layer Optimization
Power Constraint Elimination
Throughput Maximization

Performance Analysis and Evaluation
Simulation Scenario
Performance Comparisons
Impact of the Cell Population
Impact of the Primary User Traffic Load

Summary

White Space Allocation in a Cognitive Radio-Based High-Speed Vehicle Network
A Cognitive Radio-Based High-Speed Vehicle Network
System Model
Poss Loss Model
Available Channel List
Spectrum Sharing List

Maximization of Utilized White Space
Separation Computing
Branch and Bound Search Method
Single-Channel Method with Low Complexity
Linear Programming Method with Low Complexity

Performance Analysis and Evaluation
Summary

Sensing Channel Allocation in a Cognitive Radio Network for a Smart Grid
Electricity Load Shaping Framework
Smart Grid Model
The Cognitive Radio Network Model

Sensing Channel Allocation and Load Shaping Strategies
Sensing Channel Allocation Strategies
Load Shaping Strategy

Performance Analysis and Evaluation
Performance of Sensing Channel Allocation
Performance of Electricity Load Shaping

Summary
References
Index

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