End-to-end Distortion Research Articles

Designing Optimal Multiresolution Quantizers with Error Detecting Codes

This paper investigates the design of optimal multiresolution vector quantizers for broadcast channels with cyclic redundancy checks (CRC). Given a CRC-coded broadcast system with multiresolution vector quantization (MRVQ), a closed-form formula for the weighted end-to-end distortion (EED) is first derived under random index assignment. The closed-form expression is then further utilized to identify necessary optimality conditions to minimize the EED, from which an iterative algorithm is proposed for quantization design. Experiments conducted under both the point-to-point and broadcast channels demonstrate that for a wide range of channel error probability, inclusion of CRC significantly reduces the EED without sacrificing bandwidth. Further analyses are conducted to determine the best tradeoff between bits allocated for source quantization and CRC error detection.

Design and Analysis of Optimal Noisy Channel Quantization With Random Index Assignment

This paper studies the design of vector quantization on noisy channels and its high rate asymptotic performance. Given a tandem source-channel coding system with vector quantization, block channel coding, and random index assignment, a closed-form formula is first derived for computing the average end-to-end distortion (EED) of the system, which reveals a structural factor called the scatter factor of a noisy channel quantizer. Based on this formula, we propose a noisy-channel quantization design method by minimizing the EED. Experiments and simulations show that quantizers jointly designed with channel conditions significantly reduce the EED when compared with quantizers designed separately without reference to channel conditions, which reveals a practical and effective design for noisy-channel quantization as to simplify the channel model by considering a random index assignment. Furthermore, we have presented the high rate asymptotic analysis of the EED for the tandem system, while convergence analysis of the iterative algorithm is included in the Appendix.