Memory efficient adaptation of vector quantizers to time-varying channels

Channel-optimized vector quantization (COVQ) is approximated by the novel channel-adaptive scaled vector quantization (CASVQ). This new method uses a reference codebook that is optimal for one specific channel condition. However, for a bit-error rate being different from the design assumption for the reference codebook, all codevectors are scaled by a common factor, which depends on the channel condition. It is shown by simulations that a performance close to that of COVQ can be achieved in many practically important situations. Without a significant increase in complexity, the new CASVQ-scheme can be adapted to time-varying channels by adjusting the scaling factor to the current bit-error probability. Another advantage is that only one codebook needs to be stored for all error probabilities, while for COVQ either the performance degrades significantly due to channel mismatch, or a large set of codebooks must be available at the encoder and the decoder.

[1]  Hamid Jafarkhani,et al.  Channel-matched hierarchical table-lookup vector quantization for transmission of video over wireless channels , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[2]  Mikael Skoglund,et al.  Soft Decoding for Vector Quantization Over Noisy Channels with Memory , 1999, IEEE Trans. Inf. Theory.

[3]  Nariman Farvardin,et al.  On the performance and complexity of channel-optimized vector quantizers , 1991, IEEE Trans. Inf. Theory.

[4]  Kenneth Rose,et al.  Robust vector quantizer design by noisy channel relaxation , 1999, IEEE Trans. Commun..

[5]  Nariman Farvardin,et al.  A study of vector quantization for noisy channels , 1990, IEEE Trans. Inf. Theory.

[6]  Hamid Jafarkhani,et al.  Design of channel optimized vector quantizers in the presence of channel mismatch , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[7]  Kenneth Rose,et al.  Combined source-channel vector quantization using deterministic annealing , 1994, IEEE Trans. Commun..

[8]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[9]  G. Ben-David,et al.  Simple adaptation of vector-quantizers to combat channel errors , 1994, Proceedings of IEEE 6th Digital Signal Processing Workshop.

[10]  N.-J. Cheng,et al.  Robust zero-redundancy vector quantization for noisy channels , 1989, IEEE International Conference on Communications, World Prosperity Through Communications,.

[11]  Soft-decision COVQ for Rayleigh-fading channels , 1998, IEEE Communications Letters.