Joint distributed parameter and channel estimation in wireless sensor networks via variational inference

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Wireless sensor networks (WSNs) have emerged as a viable candidate for a variety of applications including military surveillance, target tracking, process monitoring, etc. A central problem in WSN is the estimation of a source parameter through a network of distributed sensors. In this work, assuming an orthogonal access channel between the sensors and the fusion center (FC), the problem of joint distributed estimation of a source parameter and channel coefficients is considered. In order to ease the complexity involved in a direct maximization of the joint posterior density, a simpler suboptimal approach is proposed using the theory of variational inference, whereby an auxiliary distribution is obtained yielding minimum Kullback-Liebler (KL) divergence with the true posterior. This results in an iterative estimation algorithm that alternates between updating the channel coefficient vector distribution and the source parameter distribution. The iterative algorithm results in a non-increasing KL divergence at each iteration, and hence, converges in divergence. The algorithm is also particularized for the case when the sensors collect noiseless observations of the source parameter. The performance of the proposed algorithm is evaluated using numerical simulations.

Original languageEnglish
Title of host publicationConference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Pages830-834
Number of pages5
DOIs
Publication statusPublished - 2012
Event46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 - Pacific Grove, CA, United States
Duration: 4 Nov 20127 Nov 2012

Other

Other46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
CountryUnited States
CityPacific Grove, CA
Period4/11/127/11/12

Fingerprint

Channel estimation
Parameter estimation
Wireless sensor networks
Sensors
Military applications
Process monitoring
Target tracking
Fusion reactions
Computer simulation

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Ahmad, A., Serpedin, E., Nounou, H., & Nounou, M. (2012). Joint distributed parameter and channel estimation in wireless sensor networks via variational inference. In Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 (pp. 830-834). [6489130] https://doi.org/10.1109/ACSSC.2012.6489130

Joint distributed parameter and channel estimation in wireless sensor networks via variational inference. / Ahmad, Aitzaz; Serpedin, Erchin; Nounou, Hazem; Nounou, Mohamed.

Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012. 2012. p. 830-834 6489130.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ahmad, A, Serpedin, E, Nounou, H & Nounou, M 2012, Joint distributed parameter and channel estimation in wireless sensor networks via variational inference. in Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012., 6489130, pp. 830-834, 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012, Pacific Grove, CA, United States, 4/11/12. https://doi.org/10.1109/ACSSC.2012.6489130
Ahmad A, Serpedin E, Nounou H, Nounou M. Joint distributed parameter and channel estimation in wireless sensor networks via variational inference. In Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012. 2012. p. 830-834. 6489130 https://doi.org/10.1109/ACSSC.2012.6489130
Ahmad, Aitzaz ; Serpedin, Erchin ; Nounou, Hazem ; Nounou, Mohamed. / Joint distributed parameter and channel estimation in wireless sensor networks via variational inference. Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012. 2012. pp. 830-834
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