Channel-optimized quantizers for decentralized detection in sensor networks

Motivated by the delay and resource constraints omnipresent in most wireless sensor network applications, we design channel-optimized scalar quantizers for a canonical decentralized detection system. Aimed at minimizing the error probability of the fusion center output, we first establish the optimality of monotone likelihood ratio partition of the observation space for the local quantizer design. We then devise an iterative algorithm to construct distributed quantizers that are person-by-person optimal. The channel-optimized approach is shown to offer better performance compared with various alternatives. It also exhibits inherent adaptivity in resource (bit) allocation in response to varying channel conditions.

[1]  D. Warren,et al.  Optimum quantization for detector fusion: some proofs, examples, and pathology , 1999 .

[2]  Krishna R. Pattipati,et al.  An algorithm for determining the decision thresholds in a distributed detection problem , 1989, Conference Proceedings., IEEE International Conference on Systems, Man and Cybernetics.

[3]  Maurizio Longo,et al.  Quantization for decentralized hypothesis testing under communication constraints , 1990, IEEE Trans. Inf. Theory.

[4]  Amy Reibman,et al.  Optimal Detection and Performance of Distributed Sensor Systems , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Peter Willett,et al.  Channel optimized binary quantizers for distributed sensor networks , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  Ramanarayanan Viswanathan,et al.  Optimal distributed decision fusion , 1989 .

[7]  Shun-ichi Amari,et al.  Statistical Inference Under Multiterminal Data Compression , 1998, IEEE Trans. Inf. Theory.

[8]  John N. Tsitsiklis,et al.  Extremal properties of likelihood-ratio quantizers , 1993, IEEE Trans. Commun..

[9]  Amy R. Reibman,et al.  Optimal Detection and Performance of Distributed Sensor Systems , 1987 .

[10]  NARIMAN FARVARDIN,et al.  Optimal quantizer design for noisy channels: An approach to combined source - channel coding , 1987, IEEE Trans. Inf. Theory.

[11]  T. Duman,et al.  Decentralized detection over multiple-access channels , 1998 .

[12]  Pramod K. Varshney,et al.  Distributed Bayesian signal detection , 1989, IEEE Trans. Inf. Theory.

[13]  Nils Sandell,et al.  Detection with Distributed Sensors , 1980, IEEE Transactions on Aerospace and Electronic Systems.

[14]  P.K. Varshney,et al.  Fusion of decisions transmitted over fading channels in wireless sensor networks , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[15]  J. Tsitsiklis.  Decentralized Detection' , 1993 .

[16]  D. Warren,et al.  Optimal Decentralized Detection for Conditionally Independent Sensors , 1989, 1989 American Control Conference.

[17]  Rick S. Blum,et al.  Exploiting the finite-alphabet property for cooperative relays , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[18]  J. Tsitsiklis.  On threshold rules in decentralized detection , 1986, 1986 25th IEEE Conference on Decision and Control.