MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems
This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent.

Organized into three chapters, the first chapter provides the background against which the system model is presented, as well as some basics concerning the channel statistics and the transmission of an OFDM signal over a multipath channel. In Chapter 2, the proposed iterative algorithm for the noise variance and the channel estimation is detailed, and in Chapter 3, an application of the algorithm for the free-band detection is proposed. In both Chapters 2 and 3, the principle of the algorithm is presented in a simple way, and more elaborate developments are also provided. The different assumptions and assertions in the developments and the performance of the proposed method are validated through simulations, and compared to methods of the scientific literature.

1124374971
MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems
This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent.

Organized into three chapters, the first chapter provides the background against which the system model is presented, as well as some basics concerning the channel statistics and the transmission of an OFDM signal over a multipath channel. In Chapter 2, the proposed iterative algorithm for the noise variance and the channel estimation is detailed, and in Chapter 3, an application of the algorithm for the free-band detection is proposed. In both Chapters 2 and 3, the principle of the algorithm is presented in a simple way, and more elaborate developments are also provided. The different assumptions and assertions in the developments and the performance of the proposed method are validated through simulations, and compared to methods of the scientific literature.

142.0 In Stock
MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems

MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems

by Vincent Savaux, Yves Louët
MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems

MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems

by Vincent Savaux, Yves Louët

eBook

$142.00 

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers

LEND ME® See Details

Overview

This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent.

Organized into three chapters, the first chapter provides the background against which the system model is presented, as well as some basics concerning the channel statistics and the transmission of an OFDM signal over a multipath channel. In Chapter 2, the proposed iterative algorithm for the noise variance and the channel estimation is detailed, and in Chapter 3, an application of the algorithm for the free-band detection is proposed. In both Chapters 2 and 3, the principle of the algorithm is presented in a simple way, and more elaborate developments are also provided. The different assumptions and assertions in the developments and the performance of the proposed method are validated through simulations, and compared to methods of the scientific literature.


Product Details

ISBN-13: 9781119007906
Publisher: Wiley
Publication date: 09/25/2014
Sold by: JOHN WILEY & SONS
Format: eBook
Pages: 136
File size: 5 MB

About the Author

Vincent Savaux is a post doctorate at Supélec in Rennes, France. He has worked in the SCEE (Signal, Communications and Embedded Electronics) team since the beginning of 2014.

Yves Louët is Professor at Supélec (SCEE team) in Rennes, France. His research activities concern the physical layer of multicarrier communication systems applied to intelligent and green radio.

Read an Excerpt

Click to read or download

Table of Contents

Introduction ix

Chapter 1. Background and System Model 1

1.1. Channel model 1

1.1.1. The multipath channel 1

1.1.2. Statistics of the channel 2

1.2. Transmission of an OFDM signal 7

1.2.1. Continuous representation 7

1.2.2. Discrete representation 9

1.2.3. Discrete representation under synchronization mismatch 12

1.3. Pilot symbol aided channel and noise estimation 12

1.3.1. The pilot arrangements 12

1.3.2. Channel estimation 15

1.3.3. Noise variance estimation 19

1.4. Work motivations 22

Chapter 2. Joint Channel and Noise Variance Estimation in the Presence of the OFDM Signal 25

2.1. Presentation of the algorithm in an ideal approach 25

2.1.1. Channel covariance matrix 25

2.1.2. MMSE noise variance estimation 27

2.1.3. Proposed algorithm: ideal approach 27

2.1.4. Simulation results: ideal approach 41

2.2. Algorithm in a practical approach 48

2.2.1. Proposed algorithm: realistic approach 48

2.2.2. Convergence of the algorithm 51

2.2.3. Simulations results: realistic approach 60

2.3. Summary 65

Chapter 3. Application of the Algorithm as a Detector For Cognitive Radio Systems 67

3.1. Spectrum sensing 67

3.1.1. Non-cooperative methods 69

3.1.2. Cooperative methods 71

3.2. Proposed detector 73

3.2.1. Detection hypothesis 73

3.2.2. Convergence of the MMSE-based algorithm under the hypothesis H0 74

3.2.3. Decision rule for the proposed detector 79

3.3. Analytical expressions of the detection and false alarm probabilities 82

3.3.1. Probability density function of M under H1 82

3.3.2. Probability density function of M under H0 85

3.3.3. Analytical expressions of Pd and Pfa 86

3.4. Simulations results 88

3.4.1. Choice of the threshold ς 88

3.4.2. Effect of the choice of eσ on the detector performance 89

3.4.3. Detector performance under non-WSS channel model and synchronization mismatch 92

3.4.4. Receiver operating characteristic of the detector 94

3.5. Summary 98

Conclusion 99

Appendices 101

Bibliography 109

Index 119

From the B&N Reads Blog

Customer Reviews