Elements of information theory
Elements of information theory
Successive structuring of source coding algorithms for data fusion, buffering, and distribution in networks
Source-channel communication in sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Multiterminal Source–Channel Communication Over an Orthogonal Multiple-Access Channel
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
Hi-index | 0.00 |
We present necessary and sufficient conditions, similar to the recent results of Gastpar [1], for the achievability of all power-distortion tuples (P, D) = (P1, P2, ... , PL, D) in an asymmetric Gaussian sensor network where L distributed sensors transmit noisy observations of a Gaussian source through a Gaussian multiple access channel to a fusion center. We show numerically that in general the gap between the provided upper bound and the lower bound of the distortion D is small. We also provide an optimal power allocation that minimizes the total power consumption, P = Σi=1L Pi, for uncoded transmission scheme while satisfying a given distortion constraint D. Numerical evaluations show that by applying the optimal power allocation uncoded transmission can perform nearly optimal in an asymmetric sensor network subject to a sum-power constraint. In the symmetric case both bounds agree and provide the optimal power-distortion tradeoff (P, D); this agrees with result of [1]. Thus, in the sense of achieving the optimal (P, D) tradeoff, uncoded transmission is optimal in the symmetric case and can be nearly-optimal in the asymmetric case.