Fundamental studies on combined coding for information source and channel

Abstract

AbstractFrom both theoretical and practical viewpoints, one of the most basic and important problems in the digital communication system is to minimize the distortion between the output signal from the information source and the destination signal on the receiving side, under the condition that the transmission rate in the channel is fixed. From such a viewpoint, this paper presents a detailed investigation of the trade‐off relation between the vector quantization (source coding) and the error‐correcting coding (channel coding), where the transmission rate of the channel is fixed as constant. The combined source and channel coding is shown, which is optimal in the sense that the average overall distortion is minimized in the communication system. The minimized average distortion is compared with the average overall distortion, where the ideal error‐correcting code with the minimum distance given by Hamming's upper bound is applied. A detailed discussion is made. The memoryless Gaussian source, the squared‐error distortion measure, the binary symmetric channel and the binary (n, k) block error‐correcting code are assumed. Finally, an investigation is made using the actual speech communication system.