Sequential source coding with side information for sensor networks
Vosoughi, A.; Scaglione, A.
Signal Processing Advances in Wireless Communications, 2007. SPAWC 2007. IEEE 8th Workshop on
Volume , Issue , 17-20 June 2007 Page(s):1 - 5
Digital Object Identifier 10.1109/SPAWC.2007.4401395
Summary:In this paper we consider the problem of estimating a vector source in a sensor network, where each sensor in the network makes a local observation of this vector source. We assume that the local observations are distorted and noise corrupted versions of the original signal source, i.e., the observation of m-th sensor ym and the signal source x are related through ym = Hmx+nm where the matrix Hm represents the distortion (filtering) effect and nm denotes the additive noise. Each sensor encodes its observation separately and sends the encoded message to a central processor (CP), whose task is to form an estimate of source x. Our objective is to design quantizers such that the distortion in the source estimate formed by the CP is minimized, subject to the sum quantization rate constraint. Realizing the resemblance of this problem to the classical CEO problem in multiterminal source coding, and inspired by the work in [S. C. Draper and G. W. Wornell, "Side information aware coding strategies for sensor networks," IEEE Journal on Selected Areas in Comm., Vol.22, No.6, pp 966-976, August 2004.], we propose a successive coding and decoding strategy, based on Wyner-Ziv coding concept. Numerical evaluation of the sum rate-distortion performance of the proposed algorithm reveals an interesting trade off between sum rate, target distortion, and number of sensor nodes which are participating in the sequential coding.
View citation and abstract |
Cart
