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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 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

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  1. Adaptive Frequency-Domain equalization for Underwater Acoustic Communications Abdelhakim Youcef Supervised by Christophe Laot and Karine Amis LabSticc seminary, Brest, February 9th , 2012

  2. 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 page 1 Abdelhakim Youcef

  3. CO Thétis • 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

  4. 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 page 3 Abdelhakim Youcef

  5. UWA communication system 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

  6. 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 page 5 Abdelhakim Youcef

  7. 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 . . . . . . . . . Abdelhakim Youcef

  8. Frequency-domain Equalization (1/3)Computational complexity page 7 Abdelhakim Youcef

  9. Frequency-domain Equalization (2/3)Cyclic 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

  10. CP 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

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

  12. 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) Input data 2N Equalizer vector N N N N samples Nzeros N Equalizer Output N . . . page 11 Abdelhakim Youcef

  13. Simulation results (1/2)OS-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

  14. Simulation results (2/2)OS-AFDE vs. CP-AFDE page 13 Abdelhakim Youcef

  15. Joint OS-AFDE and phase synchronizationMultiple 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

  16. The proposed multiple input equalizerJoint 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

  17. CO Thétis • 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

  18. Channel impulse response estimation Experiment A Experiment B page 17 Abdelhakim Youcef

  19. Experimental results (2/2)OS-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

  20. 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 page 19 Abdelhakim Youcef

  21. Questions? page 20 Abdelhakim Youcef

  22. Backup Abdelhakim Youcef

  23. The proposed multiple input equalizerJoint 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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