Adaptive Frequency-Domain equalization for Underwater Acoustic Communications

Adaptive Frequency-Domain equalization for Underwater Acoustic Communications

Abdelhakim Youcef

Supervised byChristophe Laot and Karine Amis

LabSticc seminary, Brest, February 9th , 2012

Telecom Bretagne

Introduction (1/2)UWA 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

Abdelhakim Youcefpage 2

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Introduction (2/2)

Underwater acoustic (UWA) communication:- Strong frequency selectivity (ISI)- Time-variation- Limited bandwidth (acoustic waves & transdictor )

10m

30m

-Arrival of the cable from port-Signal input

CO Thétis

15m

50m

1.5km


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Outline

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


Telecom Bretagne Abdelhakim Youcefpage 5

UWA communication system

Channel CodingQPSK

ModulationFrame

Down conversion Frequency

Domainequalizer

Timing recovery

ChannelDecoding

Transmitter

Underwater Acoustic Channel

Receiver

Source:•Image•Speech•Data

Phasesynchronizer

Adaptive processing + PLL

fc: 35kHz

Bit rate: 10 kbps

4 hydrophones

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Some applications on UWA 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



Frequency-domain Equalization (1/3)Principle

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

1C

0C

1NC

.

.

.

.

.

.

.

.

.

ky


Frequency-domain Equalization (1/3)Computational complexity

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

1,kc

N

Block of N symbolsCopy of the last symbols

CPN

CPN

Transmitter

S/PFFT IFFT P/S

nr ny

)1(kr

)(Nrk

)1(kz

)(Nzk

Nkc ,

Receiver



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)

)(log10 10CP

loss NN

NP

CP N symbols

Block of N symbolsCopy of the last symbolsCPN

(dB)


Frequency-domain Equalization (3/3)Overlap-and-save based FDE (linear model)

Each equalizer input vector contains N samples from thecurrent block and the last Samples from the previous one The first samples

correspond to a circularconvolution result

Sequence 1: incoming data blocks

Sequence 2: Equalizer vector

N zerosFFN

Initiate zeros

FFN

FFN

N

N

N N NFFN

Circular Convolutionbetween

the sequences 1 and 2 in the time-domain

The last N samples correspond to a linear convolution result

FFN


Frequency-domain Equalization (3/3)Overlap-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)

N samples N zerosN N

N

N

N

Input data 2N Equalizer vector

Equalizer Output

. . .


Simulation results (1/2)OS-AFDE vs. CP-AFDE

Bit error rate (Ber) vs. Eb/N0 calculated over 320 data blocksN = 64, = 16, number of blocks : 400, training sequence :80 data blocks

(a) Porat channel model (b) Proakis B channel model

2 4 6 8 10 12 14 1610

-4

10-3

10-2

10-1

100

Eb/N0 (dB)

Bit

err

or

rate

CP-FDE (Known channel)MMSE TDE Theoretical boundOS-AFDEAWGNCP-AFDE

2 4 6 8 10 12 14 1610

-4

10-3

10-2

10-1

100

Eb/N0 (dB)

Bit

err

or

rate

CP-FDE (known channel)MMSE TDE Theoretical boundOS-AFDEAWGNCP-AFDE

dBPloss 1)1664

64(log10 10

CPN

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Simulation results (2/2)OS-AFDE vs. CP-AFDE



Joint OS-AFDE and phase synchronizationMultiple input receiver

Adaptive processing is used to track the time-varying channel

Multiple input receiver)1(

nje

Low pass Filter

Timing recovery+

Sample rateconversion

frequency-domain equalizer

nd̂

)1(kr

sckTfje 2

)( RNnje

Oversampling

Oversampling

)()1( tx

)()( tx RN)( RN

kr

Adaptiveprocessing

frequency-domain equalizer

Low pass Filter

Timing recovery+

Sample rateconversion

sckTfje 2

skT

skT

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The proposed multiple input equalizerJoint optimization of the OS-AFDE and phase synchronization

IFFT

Delete lastblock

FFT

Delete lastblock

..

0

)1(kje

)1(kr

)1(kU

FFT IFFT)1(

kC

)( RNkje

IFFT

kd̂

ke

Append

Conjugate )1(kE

FFT

GC

)1(1kC

T

)( RNkC

Conjugate

FFT

GC

)(1RN

kC

T

)( RNkE

r r

Concatenate two blocks

)( RNkU

HNk

RU )(

H

kU )1(

)( RNkr

FFT

r r


.. y

)1(ky

Discard

.. y

)( RNky

Discard

)( jkr

0 e

)( RNkje

)1(kje

Gradient Constraint



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 buoyText sentencesv = 0.5 m/sD= 500 m

10m

30m

-Arrival of the cable from port-Signal input

CO Thétis

15m

50m

1.5km

Experiment A: •Sonar images•v = 1.4 m/s

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Channel impulse response estimation

Experiment A Experiment B



Experimental results (2/2)OS-AFDE vs. LMS-TDE

OS-AFDE: block by block equalization 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 AD=1.5 Km

Experiment BD=500 m

0 1 2 3 4 5 6 7 8 9

-16

-12

-8

-4

0

Time in s

R=4926.1084Bauds

Mea

n S

qu

are

Err

or

(dB

)

LMS-ATDEOS-AFDE

0 1 2 3 4 5 6 7 8 9

-6

-9

-3

0

Time in s

R=5747.1264Bauds

Mea

n S

qu

are

Err

or

(dB

)

Adaptive TDEOS-AFDE

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Conclusion & perspectives

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


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Questions?


Telecom Bretagnepage 22

Backup

Abdelhakim Youcef

Telecom Bretagne

The proposed multiple input equalizerJoint optimization of the OS-AFDE and phase synchronization

IFFT

Delete lastblock

FFT

Delete lastblock

..

0

)1(kje

)1(kr

)1(kU

FFT IFFT)1(

kC

)( RNkje

IFFT

kd̂

ke

Append

Conjugate )1(kE

FFT

GC

)1(1kC

T

)( RNkC

Conjugate

FFT

GC

)(1RN

kC

T

)( RNkE

r r


)( RNkU

HNk

RU )(

H

kU )1(

)( RNkr

FFT

r r


.. y

)1(ky

Discard

.. y

)( RNky

Discard

)( jkr

0 e

)( RNkje

)1(kje

Gradient Constraint


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Adaptive Frequency-Domain equalization for Underwater Acoustic Communications

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