Dimension Reduction and Expansion: Distributed Source Coding in a Noisy Environment

We studied the problem of distributed coding and transmission of intercorrelated sources with memory. Different from the conventional distributed source coding structure which relies on design of effective channel codes to model the inter-correlation and quantizer, the proposed system utilizes distributed compressed sensing [1] for signal dimension reduction through linear matrix operations and dimension expansion for protection against channel noise through a hybrid scalar quantizer linear coder [2]. The proposed system is optimized for minimum end-to-end distortion under a transmission energy constraint. Its performance is verified through simulation and can serve as a good starting point for designing similar analogue based dimension reductionexpansion schemes for applications in sensor networks.

• Type: Conference
• Year: 2008
• Where: DCC
• Authors: Anna N. Kim, Fredrik Hekland
• Keywords: Analogue Based Dimension, Computer Graphics, DCC 2008, Scalar Quantizer Linear, Signal Dimension Reduction