Optimal quantizer design for noisy channels: An approach to combined source - channel coding

Optimal detection of discrete Markov sources over discrete memoryless channels - applications to combined source-channel coding

sides of the preceding inequality by c([o(N-1) + N] log, N)-' finishes the proof. 0 ACKNOWLEDGMENT

Robustness to channel variation in source coding for transmission across noisy channels

We consider the problem of lossy source coding for transmission across an unknown or time-varying noisy channel. The objective is to design an optimal compression system for applications where the unknown channel characteristics are independently estimated at the channel encoder and decoder. Channel estimation reliability is allowed to vary from perfect channel identi cation to no channel ident...

Multiple Description Quantizer Design Using A Channel Optimized Quantizer Approach

This paper extends the channel optimized quantization scheme of Farvardin and Vaishampayan [1] to two parallel channels. The extended multiple-channel optimized quantizer design (MCOQD) framework is applied to discrete memoryless channels with erasures. The resultant MCOQD subsumes the multiple description scalar quantizer (MDSQ) design of Vaishampayan [2]. While MDSQ is suited to only “on-off”...

Robust vector quantizer design by noisy channel relaxation

This letter proposes a method to design a vector quantizer (VQ) for robust performance under noisy channel conditions. By re-optimizing the quantizer at progressively lower levels of assumed channel noise, the design is less susceptible to poor local optima. The method is applied to: 1) channel-optimized VQ design; and 2) index assignment for a source-optimized VQ. For both problems, we demonst...

Optimal nearly uniform scalar quantizer design for wavelet coding