Compression with Side Information Using Turbo Codes
DCC '02 Proceedings of the Data Compression Conference
Slepian-Wolf Coding of Multiple M-ary Sources Using LDPC Codes
DCC '04 Proceedings of the Conference on Data Compression
On Maximizing Lifetime of a Sensor Cluster
WOWMOM '05 Proceedings of the Sixth IEEE International Symposium on World of Wireless Mobile and Multimedia Networks
Approaching the Slepian-Wolf boundary using practical channel codes
Signal Processing - Special section: Distributed source coding
Distributed coding of three binary and Gaussian correlated sources using punctured turbo codes
Signal Processing - Special section: Distributed source coding
An energy-efficient adaptive DSC scheme for wireless sensor networks
Signal Processing
Cross-layer multirate interaction with distributed source coding in wireless sensor networks
IEEE Transactions on Wireless Communications
Distributed source coding using syndromes (DISCUS): design and construction
IEEE Transactions on Information Theory
Networked Slepian-Wolf: theory, algorithms, and scaling laws
IEEE Transactions on Information Theory
IEEE Communications Magazine
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This paper addresses the problem of efficient data gathering in wireless sensor networks with a complexity constrained data gathering node. Due to the complexity constraint, the data gathering node employs an asymmetric DSC that (de)compresses the data of a given node exploiting its dependency with a limited number of other nodes. This is characterized in a DSC rate allocation structure that is referred to as limited-order DSC. Within this structure, we investigate the problem of rate allocation for the nodes to maximize the network lifetime. To this end, an algorithm is proposed that is proven optimal with polynomial complexity in terms of number of network nodes. Numerical results demonstrate that the algorithm, even with limited complexity, allows for exploiting most of the achievable compression gain.