Title :
Channel-adaptive scaled vector quantization (CASVQ) for low-cost approximation of COVQ on time-varying channels
Author_Institution :
Inst. for Commun. Eng., Munich Univ. of Technol., Germany
Abstract :
Channel-optimized vector quantization (COVQ) achieves strong quality-improvements over “normal” VQ if the transmission channel is noisy. The problem addressed in this paper is how to limit the memory and complexity requirements on time-varying channels to the extent known from “normal” VQ, with a performance close to that of optimally matched COVQ for all channel conditions
Keywords :
adaptive systems; approximation theory; time-varying channels; vector quantisation; channel conditions; channel-adaptive scaled VQ; channel-adaptive scaled vector quantization; channel-optimized vector quantization; codebook; complexity requirements; low-cost approximation; memory requirements; noisy transmission channel; optimally matched COVQ; time-varying channels; Autocorrelation; Current measurement; Decoding; Distortion measurement; Error analysis; Error probability; Gaussian processes; Switches; Time-varying channels; Vector quantization;
Conference_Titel :
Information Theory, 2001. Proceedings. 2001 IEEE International Symposium on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7123-2
DOI :
10.1109/ISIT.2001.936125
