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Adaptive Frequency-Domain equalization for Underwater Acoustic Communications. Abdelhakim Youcef Supervised by Christophe Laot and Karine Amis. LabSticc seminary, Brest, February 9 th , 2012. Introduction (1/2) UWA channel. Multipath propagation (reflection at the surface and the bottom)

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Adaptive frequency domain equalization for underwater acoustic communications

Adaptive Frequency-Domain equalization for Underwater Acoustic Communications

Abdelhakim Youcef

Supervised by

Christophe Laot and Karine Amis

LabSticc seminary, Brest, February 9th , 2012


Introduction 1 2 uwa channel
Introduction (1/2) Acoustic CommunicationsUWA channel

Multipath propagation (reflection at the surface and the bottom)

Doppler effect due to the movement of the platforms

Differential Doppler effect due to the movement on the sea

Compression/dilatation of the symbol duration

Why acoustic propagation?

When the frequency increases:

The transmission range decreases (signal is attenuated)

The Doppler effect increases

Radio and optical waves are strongly attenuated

Speed of the sound

page 1

Abdelhakim Youcef


Introduction 2 2

CO Thétis Acoustic Communications

  • Arrival of the cable from port

  • Signal input

50m

15m

30m

1.5km

10m

Introduction (2/2)

  • Underwater acoustic (UWA) communication:

    • Strong frequency selectivity (ISI)

    • Time-variation

    • Limited bandwidth (acoustic waves & transdictor )

page 2

Abdelhakim Youcef


Outline
Outline Acoustic Communications

  • Underwater acoustic (UWA) communication:

  • Digital receiver for UWA communication

  • Frequency-domain equalization (FDE)

    • Cyclic-prefix adaptive FDE (CP-AFDE)

    • Overlap-and-save adaptive FDE (OS-AFDE)

    • Simulation results (CP-AFDE vs. OS-AFDE)

  • Joint OS-AFDE and phase synchronization

    • Multiple input receiver

  • Experimental results

  • Conclusions and perspectives

  • page 3

    Abdelhakim Youcef


    Uwa communication system
    UWA communication system Acoustic Communications

    Transmitter

    fc: 35kHz

    Bit rate: 10 kbps

    • Source:

    • Image

    • Speech

    • Data

    Channel Coding

    Frame

    QPSK

    Modulation

    Underwater Acoustic Channel

    4 hydrophones

    Receiver

    Frequency

    Domain

    equalizer

    Down conversion

    Phase

    synchronizer

    Timing

    recovery

    Channel

    Decoding

    Adaptive processing + PLL

    Abdelhakim Youcef


    Some applications on uwa communications
    Some applications on UWA communications Acoustic Communications

    • The off-shore oil industry

    • Aquaculture and fishing industry

    • Pollution control

    • Climate recording

    • Ocean monitoring for prediction of natural disturbances

    • Detection of objects on the ocean floor

    • Scientific data collection

    • Security and military applications

    page 5

    Abdelhakim Youcef


    Frequency domain equalization 1 3 principle
    Frequency-domain Equalization (1/3) Acoustic CommunicationsPrinciple

    • Performance: equivalent to the time-domain equalization

    • The equalization is performed block by block

    • Fast Fourier Transform (FFT) ~ circular convolution

    Serial

    To

    Parallel

    Conversion

    F

    F

    T

    I

    F

    F

    T

    Parallel

    To

    Serial

    Conversion

    .

    .

    .

    .

    .

    .

    .

    .

    .

    Abdelhakim Youcef


    Frequency domain equalization 1 3 computational complexity
    Frequency-domain Equalization (1/3) Acoustic CommunicationsComputational complexity

    page 7

    Abdelhakim Youcef


    Frequency domain equalization 2 3 cyclic prefix based fde circular model
    Frequency-domain Equalization (2/3) Acoustic CommunicationsCyclic prefix based FDE (circular model)

    N

    Block of N symbols

    Copy of the

    last

    symbols

    N

    N

    CP

    CP

    S/P

    P/S

    FFT

    IFFT

    Transmitter

    Receiver

    page 8

    Abdelhakim Youcef


    Frequency domain equalization 2 3 cyclic prefix based fde circular model1

    CP Acoustic Communications

    N symbols

    Copy of the

    last symbols

    Block of N symbols

    Frequency-domain Equalization (2/3)Cyclic prefix based FDE (circular model)

    • Advantages and properties:

      • CP length equal to the maximum channel delay spread in terms of symbol duration

      • Circular convolution in the channel

      • Removes the inter block interference

  • Inconvenient:

    • A loss in the spectral efficiency

    • Additional treatment at the transmitter (CP insertion)

  • (dB)

    Abdelhakim Youcef


    Frequency domain equalization 3 3 overlap and save based fde linear model
    Frequency-domain Equalization (3/3) Acoustic CommunicationsOverlap-and-save based FDE (linear model)

    Sequence 1: incoming data blocks

    Circular Convolution

    between

    the sequences 1 and 2

    in the time-domain

    Initiate zeros

    N

    N

    N

    N

    N

    The last N samples

    correspond to a linear

    convolution result

    The first samples

    correspond to a circular

    convolution result

    Sequence 2: Equalizer vector

    Nzeros

    Each equalizer input vector

    contains N samples from the

    current block and the last

    Samples from the previous one

    page 10

    Abdelhakim Youcef


    Frequency domain equalization 3 3 overlap and save linear model
    Frequency-domain Equalization (3/3) Acoustic CommunicationsOverlap-and-save (linear model)

    • Overlapping and sectioning methods (e.g. overlap and save)

    • The transmission of CP intervals is not necessary

    • Allows to perform linear convolution using FFT

    • The block/FFT size is selected at the receiver

    • Overlapping of 50% (block size equal to equalizer size)

    Input data 2N

    Equalizer vector

    N

    N

    N

    N samples

    Nzeros

    N

    Equalizer

    Output

    N

    . . .

    page 11

    Abdelhakim Youcef


    Simulation results 1 2 os afde vs cp afde
    Simulation results (1/2) Acoustic CommunicationsOS-AFDE vs. CP-AFDE

    (a) Porat channel model

    (b) Proakis B channel model

    Bit error rate (Ber) vs. Eb/N0 calculated over 320 data blocks

    N = 64, = 16, number of blocks : 400, training sequence :80 data blocks

    Abdelhakim Youcef


    Simulation results 2 2 os afde vs cp afde
    Simulation results (2/2) Acoustic CommunicationsOS-AFDE vs. CP-AFDE

    page 13

    Abdelhakim Youcef


    Joint os afde and phase synchronization multiple input receiver
    Joint OS-AFDE and phase synchronization Acoustic CommunicationsMultiple input receiver

    • Adaptive processing is used to track the time-varying channel

    • Multiple input receiver

    Timing recovery

    +

    Sample rate

    conversion

    Low pass

    Filter

    frequency-domain

    equalizer

    Oversampling

    Timing recovery

    +

    Sample rate

    conversion

    Low pass

    Filter

    frequency-domain

    equalizer

    Oversampling

    Adaptive

    processing

    page 14

    Abdelhakim Youcef


    The proposed multiple input equalizer joint optimization of the os afde and phase synchronization
    The proposed multiple input equalizer Acoustic CommunicationsJoint optimization of the OS-AFDE and phase synchronization

    Concatenate

    two blocks

    Gradient Constraint

    FFT

    T

    Delete last

    block

    GC

    Delete last

    block

    Conjugate

    IFFT

    Concatenate

    two blocks

    T

    GC

    Conjugate

    page 15

    Abdelhakim Youcef


    Experimental results 1 2

    CO Thétis Acoustic Communications

    • Arrival of the cable from port

    • Signal input

    50m

    15m

    30m

    • Experiment A:

      • Sonar images

      • v = 1.4 m/s

    1.5km

    10m

    Experimental results (1/2)

    • fc = 35 kHz

    • R =10 kbits/s

    • N = 32

    • Training period: 1 s

    • Pe: 180 dB ref μ Pa at 1m

    • Experiment B:

    • The transmitter is submerged and fixed at a buoy

    • Text sentences

    • v = 0.5 m/s

    • D= 500 m

    Abdelhakim Youcef


    Channel impulse response estimation
    Channel impulse response estimation Acoustic Communications

    Experiment A

    Experiment B

    page 17

    Abdelhakim Youcef


    Experimental results 2 2 os afde vs lms tde
    Experimental results (2/2) Acoustic CommunicationsOS-AFDE vs. LMS-TDE

    • OS-AFDE: block by blockequalization in the frequency-domain

    • LMS-TDE: symbol by symbol equalization in the time-domain

    • After channel decoding, the bit error rate is equal to zero

    Experiment B

    D=500 m

    Experiment A

    D=1.5 Km

    Abdelhakim Youcef


    Conclusion perspectives
    Conclusion & perspectives Acoustic Communications

    • Frequency-domain equalization: alternative to time-domain equalization

      • Computational complexity gain

      • Simple equalizer parameters setting

  • OS-AFDE vs. CP-AFDE: spectral efficiency and flexibility

  • Joint adaptive compensation of residual frequency offsets

  • Multiple input receiver

  • Influence of the block/FFT size on the performance of the OS-AFDE

  • Hybrid frequency-time domain decision Feedback equalization

  • SC-FDMA multiple access

  • page 19

    Abdelhakim Youcef


    Questions
    Questions? Acoustic Communications

    page 20

    Abdelhakim Youcef


    Backup

    Backup Acoustic Communications

    Abdelhakim Youcef


    The proposed multiple input equalizer joint optimization of the os afde and phase synchronization1
    The proposed multiple input equalizer Acoustic CommunicationsJoint optimization of the OS-AFDE and phase synchronization

    Concatenate

    two blocks

    Gradient Constraint

    FFT

    T

    Delete last

    block

    GC

    Delete last

    block

    Conjugate

    IFFT

    Concatenate

    two blocks

    T

    GC

    Conjugate

    page 22

    Abdelhakim Youcef


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