A1 Journal article (refereed)
Modeling and Mitigating Errors in Belief Propagation for Distributed Detection (2021)

Abdi, Y., & Ristaniemi, T. (2021). Modeling and Mitigating Errors in Belief Propagation for Distributed Detection. IEEE Transactions on Communications, 69(5), 3286-3297. https://doi.org/10.1109/TCOMM.2021.3056679

JYU authors or editors

Publication details

All authors or editors: Abdi, Younes; Ristaniemi, Tapani

Journal or series: IEEE Transactions on Communications

ISSN: 0090-6778

eISSN: 1558-0857

Publication year: 2021

Volume: 69

Issue number: 5

Pages range: 3286-3297

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1109/TCOMM.2021.3056679

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/75927

Web address of parallel published publication (pre-print): https://arxiv.org/abs/2004.05220


We study the behavior of the belief-propagation (BP) algorithm affected by erroneous data exchange in a wireless sensor network (WSN). The WSN conducts a distributed multidimensional hypothesis test over binary random variables. The joint statistical behavior of the sensor observations is modeled by a Markov random field whose parameters are used to build the BP messages exchanged between the sensing nodes. Through linearization of the BP message-update rule, we analyze the behavior of the resulting erroneous decision variables and derive closed-form relationships that describe the impact of stochastic errors on the performance of the BP algorithm. We then develop a decentralized distributed optimization framework to enhance the system performance by mitigating the impact of errors via a distributed linear data-fusion scheme. Finally, we compare the results of the proposed analysis with the existing works and visualize, via computer simulations, the performance gain obtained by the proposed optimization.

Keywords: distributed systems; sensor networks; wireless data transmission; signal processing; algorithms; optimisation

Free keywords: distributed systems; cooperative communications; likelihood-ratio test; communication errors; computation errors; blind signal processing; message-passing algorithms; linear data-fusion; factor graphs

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2021

Preliminary JUFO rating: 2

Last updated on 2022-17-06 at 11:27