Carrier Frequency Offset Recovery For ZERO-IF OFDM Receivers :

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  • Название:
  • Carrier Frequency Offset Recovery For ZERO-IF OFDM Receivers
  • Кол-во страниц:
  • 104
  • ВУЗ:
  • College of Graduate Studies and Research
  • Год защиты:
  • 2009
  • Краткое описание:
  • PERMISSION TO USE
    In presenting this thesis in partial fulfillment of the requirements for a Postgraduate
    degree from the University of Saskatchewan, it is agreed that the Libraries of this
    University may make it freely available for inspection. Permission for copying of this
    thesis in any manner, in whole or in part, for scholarly purposes may be granted by
    the professors who supervised this thesis work or, in their absence, by the Head of the
    Department of Electrical Engineering or the Dean of the College of Graduate Studies
    and Research at the University of Saskatchewan. Any copying, publication, or use
    of this thesis, or parts thereof, for financial gain without the written permission of
    the author is strictly prohibited. Proper recognition shall be given to the author and
    to the University of Saskatchewan in any scholarly use which may be made of any
    material in this thesis.
    Request for permission to copy or to make any other use of material in this thesis
    in whole or in part should be addressed to:
    Head of the Department of Electrical Engineering
    57 Campus Drive
    University of Saskatchewan
    Saskatoon, Saskatchewan, Canada
    S7N 5A9
    i
    ABSTRACT
    As trends in broadband wireless communications applications demand faster de-
    velopment cycles, smaller sizes, lower costs, and ever increasing data rates, engineers
    continually seek new ways to harness evolving technology. The zero intermediate
    frequency receiver architecture has now become popular as it has both economic and
    size advantages over the traditional superheterodyne architecture.
    Orthogonal Frequency Division Multiplexing (OFDM) is a popular multi-carrier
    modulation technique with the ability to provide high data rates over echo ladened
    channels. It has excellent robustness to impairments caused by multipath, which
    includes frequency selective fading. Unfortunately, OFDM is very sensitive to the
    carrier frequency offset (CFO) that is introduced by the downconversion process. The
    objective of this thesis is to develop and to analyze an algorithm for blind CFO re-
    covery suitable for use with a practical zero-Intermediate Frequency (zero-IF) OFDM
    telecommunications system.
    A blind CFO recovery algorithm based upon characteristics of the received signal’s
    power spectrum is proposed. The algorithm’s error performance is mathematically
    analyzed, and the theoretical results are verified with simulations. Simulation shows
    that the performance of the proposed algorithm agrees with the mathematical anal-
    ysis.
    A number of other CFO recovery techniques are compared to the proposed algo-
    rithm. The proposed algorithm performs well in comparison and does not suffer from
    many of the disadvantages of existing blind CFO recovery techniques. Most notably,
    its performance is not significantly degraded by noisy, frequency selective channels.
    ii
    ACKNOWLEDGMENTS
    I would like to express my sincere gratitude and appreciation to my supervisor,
    Dr. J. Eric Salt for his guidance, his teaching, and his continued patience and en-
    couragement throughout the course of Graduate Studies.
    I would also like to extend my thanks to the management and staff of TRLabs
    (Saskatoon) for their technical support, for the excellent facilities that they made
    available to me during the course of my research work, and for their financial assis-
    tance in cooperation with The National Science and Engineering Research Council
    (NSERC).
    Finally, I would like to extend special thanks to my mother and my family, for
    their continued love and endless encouragement. For without them, none of this
    would have been possible.
    iii
    Table of Contents
    PERMISSION TO USE i
    ABSTRACT ii
    ACKNOWLEDGMENTS iii
    TABLE OF CONTENTS iv
    LIST OF FIGURES viii
    LIST OF TABLES xi
    LIST OF ABBREVIATIONS xii
    1 INTRODUCTION 1
    1.1 Radio Frequency Receiver Design . . . . . . . . . . . . . . . . . . . . 1
    1.2 Orthogonal Frequency Division Multiplexing . . . . . . . . . . . . . . 2
    1.3 Carrier Frequency Offset Recovery . . . . . . . . . . . . . . . . . . . . 4
    1.4 Research Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
    1.5 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
    2 BACKGROUND INFORMATION 7
    2.1 Receiver Architectures . . . . . . . . . . . . . . . . . . . . . . . . . . 7
    2.1.1 Superheterodyne Receiver . . . . . . . . . . . . . . . . . . . . 7
    2.1.2 Zero-IF Receiver . . . . . . . . . . . . . . . . . . . . . . . . . 9
    iv
    2.2 Broadband Wireless Access . . . . . . . . . . . . . . . . . . . . . . . 10
    2.2.1 Wireless Channels . . . . . . . . . . . . . . . . . . . . . . . . 10
    2.3 Orthogonal Frequency Division Multiplexing . . . . . . . . . . . . . . 11
    2.3.1 Orthogonality . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
    2.3.2 OFDM Transmitter Model and Symbol Construction . . . . . 16
    2.4 Carrier Frequency Offset . . . . . . . . . . . . . . . . . . . . . . . . . 21
    3 ALGORITHM AND ANALYSIS 22
    3.1 Power Spectrum Analysis . . . . . . . . . . . . . . . . . . . . . . . . 22
    3.1.1 Generalized Length Power Spectrum Analysis . . . . . . . . . 27
    3.2 Algorithm Description . . . . . . . . . . . . . . . . . . . . . . . . . . 30
    3.2.1 Overview and Block Diagram . . . . . . . . . . . . . . . . . . 30
    3.2.2 Power Spectrum Estimator . . . . . . . . . . . . . . . . . . . . 31
    3.2.3 Information Band Isolator . . . . . . . . . . . . . . . . . . . . 35
    3.2.4 Carrier Frequency Offset Estimator . . . . . . . . . . . . . . . 38
    3.3 Variance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
    3.3.1 Variance Analysis of the Power Spectral Estimate . . . . . . . 39
    3.3.2 Variance Analysis of the Carrier Frequency Offset Estimator . 43
    4 ANALYSIS VERIFICATION VIA SIMULATION 51
    4.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
    v
    4.1.1 OFDM Signal Characteristics . . . . . . . . . . . . . . . . . . 51
    4.1.2 Channel Characteristics . . . . . . . . . . . . . . . . . . . . . 52
    4.1.3 Simulation Parameters . . . . . . . . . . . . . . . . . . . . . . 53
    4.2 Verification of Power Spectrum Estimator Characteristics . . . . . . . 54
    4.2.1 Power Spectrum Estimator Mean . . . . . . . . . . . . . . . . 54
    4.2.2 Power Spectrum Estimator Variance . . . . . . . . . . . . . . 56
    4.2.3 Power Spectrum Estimator Pattern-Dependent Noise Distribu-
    tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
    4.3 System Parameter Effects on CFO Estimator Variance . . . . . . . . 57
    4.3.1 Effects of the Cyclic Prefix Length . . . . . . . . . . . . . . . 59
    4.3.2 Effects of the Number of Symbols Used in the Estimator . . . 60
    4.3.3 Effects of Additive White Gaussian Channel Noise . . . . . . . 61
    4.3.4 Effects of the Modulation Type . . . . . . . . . . . . . . . . . 62
    4.3.5 Effects of the Carrier Frequency Offset Value . . . . . . . . . . 63
    5 RESULTS 64
    5.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
    5.1.1 Channel Characteristics . . . . . . . . . . . . . . . . . . . . . 65
    5.2 Algorithm Performance Comparisons . . . . . . . . . . . . . . . . . . 70
    5.2.1 CFO Estimation Based on Cyclic Prefix Correlation . . . . . . 70
    5.2.2 CFO Estimation Based on Subspace Structure . . . . . . . . . 72
    vi
    5.2.3 CFO Estimation based on Power Spectral Estimation . . . . . 74
    5.3 Performance Requirements for Practical Applications . . . . . . . . . 76
    6 CONCLUSIONS AND FUTURE WORK 79
    6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
    6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
    A MATLAB SOURCE CODE 86
    vii
    List of Figures
    2.1 Superheterodyne receiver architecture . . . . . . . . . . . . . . . . . . 8
    2.2 Zero-IF receiver architecture . . . . . . . . . . . . . . . . . . . . . . . 9
    2.3 Sample IFFT output time sequences . . . . . . . . . . . . . . . . . . 13
    2.4 DFT results for an sinusoid that is orthogonal over the interval shown 14
    2.5 DFT results for an sinusoid with delayed samples from a previous symbol 15
    2.6 DFT results for an sinusoid that is not orthogonal over the interval
    shown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
    2.7 OFDM transmitter block diagram . . . . . . . . . . . . . . . . . . . . 17
    2.8 Gray mapped QPSK and rectangular 16-QAM constellations . . . . . 18
    2.9 OFDM message symbol spectral arrangement . . . . . . . . . . . . . 20
    3.1 Illustration of the simplification of a double sum . . . . . . . . . . . . 25
    3.2 Theoretical power spectrum with varied cyclic prefix length . . . . . . 28
    3.3 Theoretical power spectrum with varied cyclic prefix length and CFO 28
    3.4 Theoretical power spectrum with DFT length varied . . . . . . . . 30
    3.5 Overall block diagram of proposed CFO estimator . . . . . . . . . . . 31
    3.6 Power spectrum partitioning . . . . . . . . . . . . . . . . . . . . . . . 32
    3.7 Block diagram of power spectrum estimator . . . . . . . . . . . . . . 32
    viii
    3.8 Illustration of data segmentation . . . . . . . . . . . . . . . . . . . . 33
    3.9 Illustration of power spectrum sampling . . . . . . . . . . . . . . . . 34
    3.10 Averaging effects of the DFT length . . . . . . . . . . . . . . . . . . . 36
    3.11 Power spectrum partitioning with transition bands shown . . . . . . . 37
    3.12 Diagram of CFO estimator block . . . . . . . . . . . . . . . . . . . . 38
    4.1 OFDM symbol spectral arrangement . . . . . . . . . . . . . . . . . . 52
    4.2 Comparison of simulated and theoretical power spectrum means in the
    information band . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
    4.3 Comparison of simulated and theoretical power spectrum means in the
    transition band . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
    4.4 Comparison of Simulated and Theoretical Power Spectrum Estimator
    Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
    4.5 PDF of one output point from the power spectrum estimator . . . . . 58
    4.6 Effect of varying the cyclic prefix length for a symbol of 256 samples . 59
    4.7 Effect of varying the number of symbols used in the CFO estimator . 60
    4.8 Effect of varying the SNR . . . . . . . . . . . . . . . . . . . . . . . . 61
    5.1 Sample Frequency response for SUI-1 low delay channel model (hilly
    terrain with high tree density) . . . . . . . . . . . . . . . . . . . . . . 66
    5.2 Sample Frequency response for SUI-4 moderate delay channel model
    (intermediate path-loss condition) . . . . . . . . . . . . . . . . . . . . 67
    ix
    5.3 Sample Frequency response for SUI-5 high delay channel model (flat
    terrain with light tree density) . . . . . . . . . . . . . . . . . . . . . . 67
    5.4 (a) Fourier series of the raised sinusoidal power spectrum; (b) Fourier
    series of a multipath channel’s frequency response; (c) Fourier series of
    the received power spectrum for a multipath channel . . . . . . . . . 68
    5.5 Effects of multipath on simulated CFO estimator performance . . . . 69
    5.6 Performance of cyclic prefix correlation based CFO estimator . . . . . 71
    5.7 Performance of subspace structure based CFO estimator . . . . . . . 73
    5.8 Proposed CFO estimator performance (SUI-4 channel) . . . . . . . . 75
    5.9 Proposed CFO estimator performance (SUI-1 and SUI-5 channels) . . 75
    5.10 Proposed algorithm performance for practical pequirements . . . . . . 78
    x
    List of Tables
    4.1 Simulation Reference Parameters . . . . . . . . . . . . . . . . . . . . 53
    5.1 Multipath Channel Model Parameters . . . . . . . . . . . . . . . . . . 66
    5.2 Tuning Parameters for Practical Performance Levels . . . . . . . . . . 77
    xi
    List of Abbreviations
    A/D Analog to Digital
    ASIC Application Specific Integrated Circuit
    CFO Carrier Frequency Offset
    D/A Digital to Analog
    DFT Discrete Fourier Transform
    DSP Digital Signal Processing
    IQ In-Phase and Quadrature
    ICI Inter-Carrier Interference
    IDFT Inverse Discrete Time Fourier Transform
    IEEE Institute of Electrical and Electronic Engineers
    IF Intermediate Frequency
    IFFT Inverse Fast Fourier Transform
    ISI Inter-Symbol Interference
    FDM Frequency Division Multiplexing
    FFT Fast Fourier Transform
    FPGA Field Programmable Gate Array
    LAN Local Area Network
    LO Local Oscillator
    LOS Line of Sight
    LNA Low Noise Amplifier
    MAN Metropolitan Area Network
    MSE Mean Squared Error
    OFDM Orthogonal Frequency Division Multiplexing
    xii
    PSD Power Spectral Density
    PSK Phase Shift Keying
    QPSK Quadrature Phase Shift Keying
    QAM Quadrature Amplitude Modulation
    RF Radio Frequency
    RFIC Radio Frequency Integrated Circuit
    SAW Surface Acoustic Wave (Filter)
    SNR Signal to Noise Ratio
    SUI Standford University Interim (Channel Model)
    xiii
    1. INTRODUCTION
    Technological advances over the past two decades have led to the rapid evolution
    of the telecommunications industry. No longer limited to narrow-band voice signals,
    modern communications integrate voice, images, data, and video on a level that was
    once considered to be impossible. As applications demand faster development cycles,
    smaller sizes, and ever increasing data rates, engineers continually seek new ways to
    harness evolving technology.
  • Список литературы:
  • 6.2 Future Work
    Compared to other blind CFO recovery algorithms in the literature, the proposed
    estimator is shown to perform very well in frequency selective channels. That said,
    improvements to the proposed algorithm’s performance and mathematical charac-
    terization could be investigated as a source of future work. In order to enhance
    performance, alternate methods of spectral estimation could be examined. One ex-
    ample would be to use overlapping and possibly windowed data segments as is done
    in Welch’s method of spectral estimation [32]. It would also be beneficial to analyze
    the variance of the estimator in greater detail given that overlapping and windowed
    segments would introduce significantly more complex correlation between segments.
    Similarly, the effects of multipath channels could be included throughout the entire
    mathematical analysis.
    82
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