Carrier Frequency Offset Recovery For ZERO-IF OFDM Receivers :

brief description

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
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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.
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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
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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.

bibliography

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
References
[1] J. Sevenhans et. al., “Trends in silicon radio large scale integration: Zero IF re-
ceiver! Zero I & Q transmitter! Zero discrete passives!”, IEEE Communications
Magazine, vol. 38, pp. 142–147, Jan 2000.
[2] Leon W. Couch II, Digital and Analog Communication Systems, Prentice Hall,
Inc., 6th Edition, 2001.
[3] D.G. Tucker, “The History of the Homodyne and the Synchrodyne”, Journal of
the British Institution of Radio Engineers, pp. 143–154, April 1954.
[4] B. Razavi, “Design considerations for direct conversion receivers”, IEEE Transactions
on Circuits and Systems II: Analog and Digital Signal Processing, vol. 44,
pp. 428–435, Jun 1997.
[5] S. Samadian et. al., “Demodulators for a zero-IF Bluetooth receiver”, IEEE
Journal of Solid-State Circuits, vol. 38, pp. 1393–1396, Aug 2003.
[6] Na Zhao et. al., “Zero-IF for GSM transmitter applications”, volume 3, pp.
1512–1514. IEEE, Apr 2008.
[7] K.J. Richter, “Zero IF satellite tuners for DBS”, IEEE Transactions on Consumer
Electronics, vol. 44, pp. 1367–1370, Nov 1998.
[8] B. Saltzberg, “Performance of an Efficient Parallel Data Transmission System”,
IEEE Transactions on Communications, vol. 15, pp. 805–811, Dec 1967.
[9] S. Fouladifard and H. Shafiee, “Frequency offset estimation in OFDM systems
in presence of IQ imbalance”, volume 3, pp. 2071–2075. IEEE, May 2003.
[10] Mingqi Li and Wenjun Zhang, “A novel method of carrier frequency offset
estimation for OFDM systems”, IEEE Transactions on Consumer Electronics,
vol. 49, pp. 965–972, Nov 2003.
[11] Zhongshan Zhang; Keping Long; Yuanan Liu, “Complex efficient carrier fre-
quency offset estimation algorithm in OFDM systems”, IEEE Transactions on
Broadcasting, vol. 50, pp. 159–164, Jun 2004.
[12] Malihe Ahmadi, “Channel estimation, data detection and carrier frequency offset
estimation in OFDM systems”, Master’s thesis, Dec 2007.
83
[13] P. Moose, “A technique for orthogonal frequency division multiplexing frequency
offset correction”, IEEE Transactions on Communications, vol. 44, pp. 2908–
2914, Oct 1994.
[14] Erchin Serpedin et. al., “Blind channel and carrier frequency offset estimation
usingperiodic modulation precoders”, IEEE Transactions on Signal Processing,
vol. 48, pp. 2389–2405, Aug 2000.
[15] Jan-Japp van de Beek et al., “ML estimation of time and frequency offset in
OFDM systems”, IEEE Transactions on Signal Processing, vol. 45, pp. 1800–
1805, Jun 1997.
[16] Biao Chen and Hao Wang, “Blind estimation of ODFM carrier frequency offset
via oversampling”, IEEE Transactions on Signal Processing, vol. 52, pp. 2047–
2057, Jul 2004.
[17] T.M. Schmidl and D.C. Cox, “Blind synchronization for OFDM”, Electronics
Letters, vol. 33, pp. 113–114, Jan 1997.
[18] H. Liu and U. Tureli, “A high-efficiency carrier estimator for OFDM communi-
cations”, IEEE Communications Letters, vol. 2, pp. 104–106, Apr 1998.
[19] Ufuk Tureli; Hui Liu; Michael D. Zoltowski, “OFDM blind carrier offset estima-
tion: ESPRIT”, IEEE Transactions on Signal Processing, vol. 52, pp. 1459–1461,
Sep 2000.
[20] IEEE Computer Society, IEEE Microwave Theory and Techniques Society, IEEE
Standard for Local and metropolitan area networks-Part 16: Air Interface for
Fixed Broadband Wireless Access Systems, IEEE, Oct 2004.
[21] Brian Minnis and Paul Moore, “A re-configurable receiver architecture for 3G
mobiles”, pp. 187–190. IEEE, 2002.
[22] P.M. Stroet et. al., “A zero-IF single-chip transceiver for up to 22Mb/s QPSK
802.11b Wireless LAN”, volume 37, pp. 204–205. IEEE, 2001.
[23] Eric Pellet, “Signal Distortion Cause By Tree foliage in a 2.5 GHz Channel”,
Master’s thesis, Nov 2003.
[24] V. Erceg et. al., Channel Models for Fixed Wireless Applications, IEEE, 2003.
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