认知无线电网络中的动态频谱接入与管理

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xiv Preface

researchers in both academia and industry, and engineers in the wireless industry, as

well as from spectrum policy makers.

Design, analysis, and optimization of dynamic spectrum access require multidis-

ciplinary knowledge, namely, knowledge of wireless communication and networking,

signal processing, artiﬁcial intelligence (e.g. for learning), decision theory, optimization,

and economic theory. A comprehensive introduction to the dynamic spectrum access

and spectrum management problem in a cognitive radio network therefore needs to cover

the basic concepts/theories for designing dynamic spectrum access methods as well as

state-of-the-art of dynamic spectrum access and management methods.

This book provides a comprehensive treatment of the dynamic spectrum access and

spectrum management problem in cognitive radio networks. The topics covered include

the following: introduction to cognitive radio and the basic concepts of dynamic spectrum

access; the analysis, design, and optimization of dynamic spectrum access techniques

for cognitive radio; and state-of-the-art of dynamic spectrum access techniques. The key

features of this book are as follows:

a uniﬁed view of dynamic spectrum access for cognitive radio networks,

coverage of a wide range of techniques for design, analysis, and optimization of

dynamic spectrum access for cognitive radio networks,

comprehensive treatment of state-of-the-art dynamic spectrum access techniques, and

outlining the key research issues related to dynamic spectrum access.

The book is divided into three parts: Part I (Introduction), Part II (Techniques for

design, analysis, and optimization of dynamic spectrum access and management), and

Part III (Dynamic spectrum access and management). Part I comprises Chapters 1 and

2, which provide an introduction to the different wireless technologies and cognitive

radio networks. The topics covered include the basics of cellular wireless, wireless local

area network (WLAN), wireless metropolitan area network (WMAN), wireless personal

area network (WPAN), wireless regional area network (WRAN) technology and related

standards; the basic components, features, and potential applications of cognitive radio;

an introduction to dynamic spectrum access; the motivations for cognitive radio-based

wireless access technology; and the research issues in the different layers of the protocol

stack for a cognitive radio network.

In Part II, different techniques which can be applied to the problem of the design,

analysis, and optimization of dynamic spectrum access mechanisms in cognitive radio

networks are introduced. In Chapter 3, the signal processing techniques (e.g. techniques

for parameter estimation, ﬁltering, and prediction) which are required for a wireless node

to observe and gain knowledge of the ambient radio environment in order to access the

radio spectrum dynamically are described. Optimization techniques, which are useful

to obtain the optimal dynamic spectrum management scheme, are discussed in Chap-

ter 4. Major variations of optimization techniques (e.g. unconstrained and constrained

optimization, non-linear optimization, combinatorial optimization) are presented. Also,

stochastic optimization based on dynamic programming, the Markov decision process

(MDP), and stochastic programming for dynamic spectrum access in a random radio

environment are discussed. In Chapter 5, game theory techniques are discussed in the

Preface xv

context of designing dynamic spectrum access methods. Game theory is an attractive tool

to model the dynamic spectrum sharing problem in a cognitive wireless network. The

basics of different game theory models, namely, non-cooperative, repeated, cooperative

(i.e. bargaining and coalition), and evolutionary game models are presented. Intelligent

algorithms (i.e. learning techniques) are fundamental to cognitive radio design, and pro-

vide the ability to observe, learn, plan, and optimize the decision of dynamic spectrum

access in a cognitive radio network. An introduction to different machine learning tech-

niques including supervised learning, unsupervised learning, and reinforcement learning

is provided in Chapter 6. Example applications of these techniques are discussed in the

context of cognitive radio. Intelligent techniques based on genetic algorithms and fuzzy

control are also discussed.

Part III deals with the modeling, design, and analysis of dynamic spectrum access

and management schemes in cognitive radio networks. In Chapter 7, different models

of spectrum access/sharing are discussed. Different approaches for spectrum sensing,

which is a key component of dynamic spectrum access, are reviewed. A comprehensive

review of the different medium access control (MAC) protocols developed for dynamic

spectrum access is presented. Dynamic spectrum access and management architectures

can be either centralized or distributed. In the centralized approach, a central controller

collects information about the radio environment and controls the spectrum access by

cognitive radio users. In Chapter 8, different schemes for centralized dynamic spectrum

access are reviewed. Chapter 8 also introduces the concept of spectrum auction, which

requires a centralized auctioneer for dynamic spectrum access and management. If there

is no central controller available in a cognitive radio network, the cognitive radio users

have to make their spectrum access decisions independently in a distributed manner.

Chapter 9 introduces the concept of distributed dynamic spectrum access. Two major

approaches to distributed dynamic spectrum access, namely, the cooperative and the non-

cooperative approach are discussed. Chapter 10 deals with the application of learning

algorithms in distributed dynamic spectrum access. The signaling protocols required

to support distributed spectrum access are also reviewed. While dynamic spectrum

access and management can be designed by considering only the technical issues,

the economic issues are also important, especially under the new spectrum licensing

paradigm. Chapters 11 and 12 address the economic aspects of spectrum sharing and

management in a cognitive radio network. Chapter 11 introduces the concept of spectrum

trading and reviews the different spectrum trading schemes. Through spectrum trading,

the licensed users (or primary service provider) are able to sell a portion of the unused

spectrum to the unlicensed users (or secondary service provider). The basic economic

theories which can be used in dynamic spectrum access are reviewed. Chapter 12 provides

an extensive review of economics-inspired dynamic spectrum access and management

models. The ﬁrst two models are based on competitive dynamic spectrum access and

pricing. The concept of collusion among cognitive radio users in the context of spectrum

trading is discussed. A spectrum trading model for IEEE 802.22-based wireless regional

area networks (WRANs) is presented.

To use this book, if the reader is familiar with wireless technologies and the concept

of cognitive radio, the ﬁrst chapter can be skipped. Also, if the reader is an experienced

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