Distributed detection in practical wireless sensor networks via a two-step consensus algorithm

The problem of fully distributed detection of an unknown deterministic signal observed by a wireless sensor network (WSN) is addressed. We propose a two-step distributed consensus-based detection algorithm where in the first step the sensor nodes (SNs) collaborate with their neighbors through error-free, orthogonal channels (the SNs exchange quantized information matched to the channel capacity of each link). In the second step, local 1-bit decisions generated in the first step are shared among neighbors to yield a consensus. Simulations show that our proposed quantized two-step distributed detection algorithm approaches the performance of the unquantized centralized (fusion center) detector.

[1]  Philippe Ciblat,et al.  Fully distributed signal detection: Application to cognitive radio , 2013, 21st European Signal Processing Conference (EUSIPCO 2013).

[2]  Natalia A. Schmid,et al.  Optimal power allocation for distributed blue estimation with linear spatial collaboration , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[3]  Pramod K. Varshney,et al.  A decentralized framework for linear coherent estimation with spatial collaboration , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[4]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[5]  Soummya Kar,et al.  Topology for Distributed Inference on Graphs , 2006, IEEE Transactions on Signal Processing.

[6]  Ali H. Sayed,et al.  Diffusion LMS Strategies for Distributed Estimation , 2010, IEEE Transactions on Signal Processing.

[7]  Pramod K. Varshney,et al.  Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks , 2006, IEEE Transactions on Signal Processing.

[8]  Mounir Ghogho,et al.  Optimal quantization and power allocation for energy-based distributed sensor detection , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

[9]  Shilian Zheng,et al.  Distributed consensus algorithms for decision fusion based cooperative spectrum sensing in cognitive radio , 2011, 2011 11th International Symposium on Communications & Information Technologies (ISCIT).

[10]  Marc Moonen,et al.  Distributed computation of the Fiedler vector with application to topology inference in ad hoc networks , 2013, Signal Process..

[11]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[12]  Sergio Barbarossa,et al.  Distributed Detection and Estimation in Wireless Sensor Networks , 2013, ArXiv.

[13]  H. Urkowitz.  Energy detection of unknown deterministic signals , 1967 .

[14]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[15]  Ioannis D. Schizas,et al.  Distributed LMS for Consensus-Based In-Network Adaptive Processing , 2009, IEEE Transactions on Signal Processing.

[16]  Mounir Ghogho,et al.  Quantized fusion rules for energy-based distributed detection in wireless sensor networks , 2014, 2014 Sensor Signal Processing for Defence (SSPD).

[17]  Zheng Wang,et al.  Distributed Cooperative Spectrum Sensing Based on Weighted Average Consensus , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.