Adaptive MMSE Multiuser Receivers in MIMO OFDM MMSE Multiuser Receivers in MIMO OFDM Wireless Communication Systems by ... MLSE Maximum

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  • Adaptive MMSE Multiuser Receivers in MIMO

    OFDM Wireless Communication Systems


    Titus Ikechukwu ENEH


    Submitted to the University of Greenwich

    in partial fulfilment of the requirements

    for admission to the degree of

    Doctor of Philosophy

    Medway School of Engineering

    June 2011


    I certify that this work has not been accepted in substance for any degree, and is not

    concurrently being submitted for any degree other than that of Doctor of Philosophy

    (PhD) being studied at the University of Greenwich. I also declare that this work is

    the result of my own investigations except where otherwise identified by references

    and that I have not plagiarized the work of others.

    Signed ........................................, Date .....................................

    Titus Ikechukwu Eneh


    Signed ........................................, Date .....................................

    Prof. Predrag Rapajic

    (Ist supervisor)

    Signed ........................................, Date .....................................

    Dr Re-wu

    (2nd supervisor).



    This project over the last four years is by far, the most significant accomplishment

    of my life and it would be impossible without people who supported and believed

    in me.

    My utmost gratitude goes to the ancient of days, the Almighty God, the

    author of life who has enabled and provided me with the opportunity to embark on

    this journey of acquisition of knowledge. May His name be forever praised.

    My heartfelt appreciations and deepest thanks goes to my amiable supervisor,

    Professor Predrag Rapajic for his expert guidance. His approach to research work is

    professional and his support throughout my PhD was phenomenal and tremendous.

    His vast knowledge in Engineering, especially wireless communications, and his skills

    in research paper writing is overwhelming. His belief in me and the various privileges

    he had given to me have helped to bring me to this end. He found time to proffer

    invaluable suggestions and advice towards the realization of this research work. It

    will be an understatement to say I have gained immensely from his pool of knowledge

    and persistent encouragement during the course of my PhD work.

    I would like to express my heartfelt gratitude to the only love of my life,

    my angel, sweet Uzomaka Goretti ENEH for her understanding and total support

    at every stage of this PhD work. You are more than a wife to me. Thank you

    very much. Special appreciation to my lovely twins (Terry and Bliss) whom have

    continued to shower their love and disturbances throughout my PhD work.

    I wish to express my special thanks to Mr Emeka Eneh (Akwaeke), Mr Obi

    Chime and Prof. Ezeugwu of University of Southbank Uk for their candid support

    from the start to the finish of this work.


  • My Special thanks goes to Prof. ND Ekere, Head of school, Medway School

    of Engineering, UoG , Dr Steve Woodhead, Director of Research, Medway School of

    Engineering and Dr Raj Bhatti for their support and assistance over the years.

    I must also acknowledge my fellow PhD students: Dr Raam Balasub-ramanyam

    , Dr.Trianthafylos. Kanakis (Aldo), Kwashie Amartei Anang, Athar Qureshi, Yo-

    gesh Nijsure, Lawal Bello, Grace Oletu, Kojo Peter Banasko, Emeka Amalu, Kenny

    Otiaba, Mathias Ekpu, Joy Adeyemi, Shangtong Yang and Andrew Adekunle for

    their help, friendship and encouragement during the course of my PhD work.

    A very special thanks to my sick mother (Mrs Christiana Ekpeluchi ENEH)

    for her prayers and understanding. My brothers Dozie.P, John. C, James. I and

    Herbert. E (ENEH) and their families. My sisters J. N. Jideofor and Eugenia. I

    Iloh and their families, for all the support they have provided for me through out

    my entire life. My in-laws Mr and Mrs .C. Izueke and family for their prayers and


    I would also like to thank all the friends I made in United Kingdom, from

    around the world, for supporting me and giving me the strength to carry on with

    this research.

    This report writing will not be complete, if I fail to express my gratitude to

    Medway School of Engineering, University of Greenwich, as without their assistance

    this research would not have been possible, if not the financial assistance and the

    scholarship provided.

    Mobile and Wireless Communication Engineering

    School of Engineering, University of Greenwich

    Chatham Dockyard, Medway City, Kent

    London, United Kingdom

    ME4 4TB

    May 2011

    Titus. I. ENEH



    In a bid to cope with challenges of increasing demand for higher data rate,

    better quality of service, and higher network capacity, there is a migration from

    Single Input Single Output (SISO) antenna technology to a more promising Multiple

    Input Multiple Output (MIMO) antenna technology. On the other hand, Orthogonal

    Frequency Division Multiplexing (OFDM) technique has emerged as a very popular

    multi-carrier modulation technique, thus it is considered as a promising solution to

    enhance the data rate of future broadband wireless communication systems.

    The first contribution of this thesis is the development of a low complexity

    adaptive algorithm that is robust against slow and fast fading channel scenarios,

    in comparison to the conventional individual parameter estimation by E. Teletar in

    his famous paper of 1999. Implementing the Adaptive MMSE Receivers in MIMO

    OFDM systems which I refer to (AMUD MIMO OFDM), combines the adaptive

    minimum mean square error multiuser receivers scheme with prior information of

    the channel and interference cancelation in the spatial domain, achieves enhanced

    joint channel estimation and signal detection which makes the new technique effec-

    tively mobile.

    A mathematical analysis and simulation results to estimate the Information

    Capacity of Mobile Communication system with MMSE DFE and OFDM receivers

    were investigated. The capacity of a stationary channel with ISI is achievable by

    both the single carrier MMSE DFE and multicarrier modulation over narrow sub

    channels with OFDM receivers. The achieved capacity result shows that in both

    techniques single carrier and multicarrier, apart from different implementations are


  • essentially identical when it comes to achievable criteria for information channel


    Lastly, AMUD MIMO OFDM were compared with both adaptive vector pre-

    coding and iterative system and their performance were fantastic, results shows that

    it will assure transmission over a high channel capacity.



    ADSL Asynchronous Digital Subscriber Line

    AMUD Adaptive Multiuser Detection

    AWGN Additive White Gaussian Noise

    BER Bit Error Rate

    BPSK Binary Phase Shift Keying

    CDMA Code Division Multiple Access

    CP Cyclic Prefix

    CSI Channel State Information

    DAB Digital Audio broadcast

    DFE Decision Feedback Equalization

    DMT Discrete Multitone

    DVB Digital Video broadcast

    ETSI European Telecommunication Standards Institute

    FEC Forward Error Correction

    FIR Finite Impulse Responds

    HIPERLAN High Performance Radio Local Area Networks

    ICI Intercarrier Interference

    IEEE Institute of Electrical and Electronics Engineers

    IIR Infinite Impulse Response

    iid Independent Identically Distributed

    ISI Inter Symbol Interference


  • LS Least Square

    LAN Local Area Network

    LMS Least Mean Square

    MAC Medium Access Control

    MAI Multiple Access Interference

    MAP Maximum a Posteriori

    MBPS Megabite per Second

    MC Multicarrier

    MCM Multi-carrier Modulation

    MF Matched Filter

    MIMO Multiple Input Multiple Output

    MISO Multiple Input Single Output

    MLSE Maximum Likelihood Sequence Estimator

    MMSE Minimum Mean Square Error

    MMSE DFE Minimum Mean Square Decision Feedback Equalization

    MRC Maximum Ratio Combiner

    MSE Mean Square Error

    MUD Multiuser Detector

    MUI Multi-User Interference

    OFDM Orthogonal Frequency Division Multiplexing

    PIC Picture Interference Cancellation

    QAM Quadrature Amplitude Modulation

    RF Radio Frequency

    RLS Recursive Least Square

    SIC Successive Interference Cancellation

    SIMO Single Input Multiple Output

    SINR Signal to Interference Noise Ratio

    SISO Single Input Single Output


  • SNR Signal to Noise Ratio

    STBC Space Time Block Code

    SVD Singular Value Decomposition

    VLSI Very Large Scale Integration

    WLAN Wireless Local Area Networks

    WSS Wide Sense Stationary

    ZF Zeroforcing

    ZMCSCG Zero Mean Circular Symmetric Complex Gaussian



    AH Complex Conjugate transpose (Hermitian transpose) of a matrix A

    aH Complex Conjugate transpose (Hermitian transpose) of a vector a

    | A | Determinant of a matrix A

    E [A] Probabilistic expectation of a Matrix A

    min(A) Smallest eigen value of Matrix A

    max(A) Largest eigen value of matrix A

    tr{A} trace of a Matrix A

    AB Kronecker product of Matrices A, B

    In n x n identity matrix

    21 Unit Variance

    Threshold level

    Hij Channel Frequency response

    R Correlation Matrix

    Mn Gradient

    opt Optimum (Wiener solution) Linear and DFE

    H Toep