Nonlinear coding and estimation for correlated data in wireless sensor networks

The problem of designing simple and energy efficient nonlinear distributed source-channel codes is considered. By demonstrating similarities between this problem and the problem of bandwidth expansion, a structure for source-channel codes is presented and analyzed. Based on this analysis an understanding about desirable properties for such a system is gained and used to produce an explicit source-channel code which is then analyzed and simulated. One of the main advantages of the proposed scheme is that it is implementable for many sources, contrary to most existing nonlinear distributed source-channel coding systems.

[1]  James S. Lehnert,et al.  TCM/SSMA communication systems with cascaded sequences and PAM/QAM signal sets , 1998, IEEE Trans. Commun..

[2]  Mikael Skoglund,et al.  Nonlinear distributed source-channel coding over orthogonal additive white Gaussian noise channels , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[3]  Michael Gastpar,et al.  Source-Channel Communication in Sensor Networks , 2003, IPSN.

[4]  Kenneth Rose,et al.  Distributed Predictive Coding for Spatio-Temporally Correlated Sources , 2009, IEEE Transactions on Signal Processing.

[5]  R. A. McDonald,et al.  Noiseless Coding of Correlated Information Sources , 1973 .

[6]  Sueli I. Rodrigues Costa,et al.  Curves on a sphere, shift-map dynamics, and error control for continuous alphabet sources , 2003, IEEE Transactions on Information Theory.

[7]  Aaron D. Wyner,et al.  Recent results in the Shannon theory , 1974, IEEE Trans. Inf. Theory.

[8]  Mikael Skoglund,et al.  Distributed quantization over noisy channels , 2009, IEEE Transactions on Communications.

[9]  I. Bahceci,et al.  Energy-Efficient Estimation of Correlated Data in Wireless Sensor Networks , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[10]  Zixiang Xiong,et al.  Compression of binary sources with side information at the decoder using LDPC codes , 2002, IEEE Communications Letters.

[11]  M. Skoglund,et al.  Analog Source-Channel Codes Based on Orthogonal Polynomials , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[12]  Zhi-Quan Luo,et al.  Optimal linear decentralized estimation in a bandwidth constrained sensor network , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[13]  K. Ramchandran,et al.  Distributed source coding using syndromes (DISCUS): design and construction , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[14]  Ying Zhao,et al.  Compression of correlated binary sources using turbo codes , 2001, IEEE Communications Letters.

[15]  Zixiang Xiong,et al.  Nested quantization and Slepian-Wolf coding: a Wyner-Ziv coding paradigm for i.i.d. sources , 2004, IEEE Workshop on Statistical Signal Processing, 2003.

[16]  Andrea J. Goldsmith,et al.  Estimation Diversity and Energy Efficiency in Distributed Sensing , 2007, IEEE Transactions on Signal Processing.

[17]  Sailes K. Sengijpta Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[18]  Kannan Ramchandran,et al.  Generalized coset codes for distributed binning , 2005, IEEE Transactions on Information Theory.

[19]  Mikael Skoglund,et al.  Polynomial based analog source-channel codes , 2009 .

[20]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[21]  Michael Gastpar,et al.  Uncoded transmission is exactly optimal for a simple Gaussian "sensor" network , 2008, 2007 Information Theory and Applications Workshop.

[22]  Gregory W. Wornell,et al.  Analog error-correcting codes based on chaotic dynamical systems , 1998, IEEE Trans. Commun..

[23]  David J. Sakrison,et al.  Solution manual for problems in Communication theory : transmission of waveforms and digital information , 1968 .

[24]  I. M. Jacobs,et al.  Principles of Communication Engineering , 1965 .

[25]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[26]  Zhi-Quan Luo,et al.  Multiterminal Source–Channel Communication Over an Orthogonal Multiple-Access Channel , 2007, IEEE Transactions on Information Theory.