Censored distributed space-time coding for wireless sensor networks
EURASIP Journal on Advances in Signal Processing
Decentralised binary detection with non-constant SNR profile at the sensors
International Journal of Sensor Networks
Peer-to-peer estimation over wireless sensor networks via Lipschitz optimization
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
State estimation with quantized measurements in wireless sensor networks
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
State estimation with quantized measurements in wireless sensor networks
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Low-complexity algorithms for event detection in wireless sensor networks
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
IEEE Transactions on Signal Processing
Brief paper: An efficient sensor quantization algorithm for decentralized estimation fusion
Automatica (Journal of IFAC)
Decentralized Estimation using distortion sensitive learning vector quantization
Pattern Recognition Letters
| Hi-index | 0.01 |
Consider the problem of decentralized detection with a distributed sensor network where the communication channels between sensors and the fusion center are bandwidth constrained. Previous approaches to this problem typically rely on quantization of either the sensor observations or the local likelihood ratios, with quantization levels optimally designed using the knowledge of noise distribution. In this paper, we assume that each sensor is restricted to send a 1-bit message to the fusion center and that the sensor noises are additive, zero mean, and spatially independent but otherwise unknown and with possibly different distributions across sensors. We construct a universal decentralized detector using a recently proposed isotropic decentralized estimation scheme , that requires only the knowledge of either the noise range or its second-order moment. We show that the error probability of this detector decays exponentially at a rate that is lower bounded either in terms of the noise range for bounded noise or the signal-to-noise ratio for noise with unbounded range.