%0 Generic
%A Del Ser, Javier
%A Mendicute, Mikel
%A Crespo, Pedro M.
%A Gil-Lopez, Sergio
%A Olabarrieta, Ignacio
%T Joint source-channel-network decoding and blind estimation of correlated sensors using concatenated zigzag codes
%J Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
%D 2009
%@ 0302-9743
%U https://hdl.handle.net/11556/1647
%X Focusing on densely deployed wireless sensor networks, this paper presents a novel method for joint source-channel-network coding of distributed correlated sources through multiple access relay channels. In such networks, the role of intermediate sensors as relay nodes permits to achieve enhanced end-to-end error performance and increased spatial diversity in presence of channel fading. This paper addresses this scenario for a two source, single relay architecture by proposing a novel coding approach based on concatenated Zigzag codes, whose low complexity is specially suitable for energy-constrained autonomous systems. Joint decoding and estimation of the parameters defining the correlation between sensors is iteratively performed at the receiver side. Simulation results show that the proposed joint coding scheme attains significant energy gains with respect to traditional routing techniques, specially at high signal to noise ratios.
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