Dynamic Spectrum Management

From Cognitive Radio to Blockchain and Artificial Intelligence

Author: Ying-Chang Liang

Publisher: Springer Singapore

Book Series : Signals and Communication Technology

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Table of Contents

About this book

This open access book, authored by a world-leading researcher in this field, describes fundamentals of dynamic spectrum management, provides a systematic overview on the enabling technologies covering cognitive radio, blockchain, and artificial intelligence, and offers valuable guidance for designing advanced wireless communications systems. This book is intended for a broad range of readers, including students and professionals in this field, as well as radio spectrum policy makers.

Frontmatter

PDF

Open Access

Chapter 1. Introduction

Abstract

Facing the increasing demand of radio spectrum to support the emerging wireless services with heavy traffic, massive connections and various quality-of-services (QoS) requirements, the management of spectrum becomes unprecedentedly challenging nowadays. Given that the traditional fixed spectrum allocation policy leads to an inefficient usage of spectrum, the dynamic spectrum management (DSM) is proposed as a promising way to mitigate the spectrum scarcity problem. This chapter provides an introduction of DSM by firstly discussing its background, then presenting the two popular models: the opportunistic spectrum access (OSA) model and the concurrent spectrum access (CSA) model. Three main enabling techniques for DSM, including the cognitive radio (CR), the blockchain and the artificial intelligence (AI) are briefly introduced.

Ying-Chang Liang

PDF View full text

Open Access

Chapter 2. Opportunistic Spectrum Access

Abstract

Opportunistic spectrum access (OSA) model is one of the most widely used model for dynamic spectrum access. Spectrum sensing is the enabling function for OSA. The inability for a secondary user (SU) to perform spectrum sensing and spectrum access at the same time requires a joint design of sensing and access strategies to maximize SUs’ own desire for transmission while ensuring sufficient protection to the primary users (PUs). This chapter starts with a brief introduction on the opportunistic spectrum access model and the functionality of sensing-access design at PHY and MAC layers. Then three classic sensing-access design problems are introduced, namely, sensing-throughput tradeoff, spectrum sensing scheduling, and sequential spectrum sensing. Finally, the application of the opportunistic spectrum access to operating LTE in unlicensed band (LTE-U) is discussed.

Ying-Chang Liang

PDF View full text

Open Access

Chapter 3. Spectrum Sensing Theories and Methods

Abstract

Spectrum sensing is a critical step in cognitive radio based DSM to learn the radio environment. Despite its long history, in the past decade, the study on spectrum sensing has attracted substantial interests from the wireless communications community. In this chapter, we first provide the fundamental theories on spectrum sensing from the optimal likelihood ratio test perspective, then we review the classical methods including Bayesian method, robust hypothesis test, energy detection, matched filtering detection, and cyclostationary detection. After that, we discuss the robustness of the classical methods and review techniques that can enhance the sensing reliability under hostile environment. These methods include eigenvalue based sensing method, covariance based detection method. Finally, we discuss the cooperative sensing that uses data fusion or decision fusion from multiple senors to enhance the sensing performance.

Ying-Chang Liang

PDF View full text

Open Access

Chapter 4. Concurrent Spectrum Access

Abstract

Concurrent spectrum access (CSA), which allows different communication systems simultaneously transmit on the same frequency band, has been recognized as one of the most important techniques to realize the dynamic spectrum management (DSM). By regulating the interference to be received by primary users, the secondary users are able to gain continuous transmission opportunity. Without the need of frequent spectrum detection and reconfiguration, the CSA has the merit of low cost and easy implementation in practice. In this chapter, we will present some important CSA models, discuss the key problems existing in these CSA systems, and review the techniques to deal with these problems.

Ying-Chang Liang

PDF View full text

Open Access

Chapter 5. Blockchain for Dynamic Spectrum Management

Abstract

Blockchain is believed to bring new opportunities to dynamic spectrum management (DSM). With features of blockchain, the traditional spectrum management method, such as the spectrum auction, can be improved. It can also help to overcome the challenges about the security or the lack of incentive mechanisms for collaboration in DSM. Moreover, with blockchain, spectrum usage of the DSM system can be recorded in a decentralized manner. In this chapter, we will discuss the potentials of blockchain for spectrum management in a systematic way and using multiple case studies.

Ying-Chang Liang

PDF View full text

Open Access

Chapter 6. Artificial Intelligence for Dynamic Spectrum Management

Abstract

In the past decade, a significant advancement has been made in artificial intelligence (AI) research from both theoretical and application perspectives. Researchers have also applied AI techniques, particularly machine learning (ML) algorithms, to DSM, the results of which have shown superior performance as compared to traditional ones. In this chapter, we first provide a brief review on ML techniques. Then we introduce recent applications of ML algorithms to enablers of DSM, which include spectrum sensing, signal classification and dynamic spectrum access.

Ying-Chang Liang

PDF View full text

Title: Dynamic Spectrum Management
Author: Ying-Chang Liang
Publisher: Springer Singapore
Electronic ISBN: 978-981-15-0776-2
Print ISBN: 978-981-15-0775-5
DOI: https://doi.org/10.1007/978-981-15-0776-2