Data Compression Conference (dcc 2008)
Dimension Reduction and Expansion: Distributed Source Coding in a Noisy Environment
March 25-March 27
ISBN: 978-0-7695-3121-2
We studied the problem of distributed coding and transmission of inter-correlated 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 [DCS06] for signal dimension reduction through linearmatrix operations and dimension expansion for protection against channel noise through a hybrid scalar quantizer linear coder [Coward00]. The proposed system is optimized for minimum end-to-end distortion under a transmission energy constraint. Itsperformance is verified through simulation and can serve as a good starting point for designing similar analogue based dimension reduction-expansion schemes for applications in sensor networks.
Index Terms:
Distributed Source Coding, Compressed Sensing, dimension reduction/expansion, joint source-channel coding
Citation:
Anna N. Kim, Fredrik Hekland, "Dimension Reduction and Expansion: Distributed Source Coding in a Noisy Environment," dcc, pp.332-341, Data Compression Conference (dcc 2008), 2008