Joint adaptive quantization and fading channel estimation for target tracking in wireless sensor networks

Majdi Mansouri, Hichem Snoussi, Cédric Richard

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

1 Citation (Scopus)

Abstract

We consider the problem of target tracking in wireless sensor networks where the observed system is assumed to progress respecting to a probabilistic state space model. We propose to improve the use of the quantized variational filtering (QVF) by jointly optimize the quantization level and estimate the path-loss between sensors. Recently, quantized variational filtering QVF has been proved to be adapted to the communication constraints of sensor networks. Its efficiency relies on the fact that the online update of the filtering distribution and its compression are executed simultaneously. Our proposed technique is developed to jointly optimize the quantization level and estimate the path-loss coefficient, where the sensors are connected with unknown fading channels. First, sensors observations are quantized under a constant transmitting power constraint. This quantization is performed by online maximizing the predictive Fisher Information (FI). Then, we estimate the path-loss coefficient by maximizing its a posteriori distribution. The simulation results show that the joint adaptive quantization and fading channel estimation algorithm, for the same sensor transmitting power, outperforms both the VF algorithm using a fixed optimal quantization level and the VF algorithm based on binary sensors.

Original languageEnglish
Title of host publicationIEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009
Pages612-615
Number of pages4
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event9th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009 - Ajman, United Arab Emirates
Duration: 14 Dec 200916 Dec 2009

Other

Other9th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009
CountryUnited Arab Emirates
CityAjman
Period14/12/0916/12/09

Fingerprint

Channel estimation
Target tracking
Fading channels
Wireless sensor networks
Sensors
Sensor networks
Communication

Keywords

  • Adaptive algorithm
  • Fading channel
  • Maximum a posteriori
  • Quantized variational filtering
  • Wireless sensor networks

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Mansouri, M., Snoussi, H., & Richard, C. (2009). Joint adaptive quantization and fading channel estimation for target tracking in wireless sensor networks. In IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009 (pp. 612-615). [5407552] https://doi.org/10.1109/ISSPIT.2009.5407552

Joint adaptive quantization and fading channel estimation for target tracking in wireless sensor networks. / Mansouri, Majdi; Snoussi, Hichem; Richard, Cédric.

IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009. 2009. p. 612-615 5407552.

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

Mansouri, M, Snoussi, H & Richard, C 2009, Joint adaptive quantization and fading channel estimation for target tracking in wireless sensor networks. in IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009., 5407552, pp. 612-615, 9th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009, Ajman, United Arab Emirates, 14/12/09. https://doi.org/10.1109/ISSPIT.2009.5407552
Mansouri M, Snoussi H, Richard C. Joint adaptive quantization and fading channel estimation for target tracking in wireless sensor networks. In IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009. 2009. p. 612-615. 5407552 https://doi.org/10.1109/ISSPIT.2009.5407552
Mansouri, Majdi ; Snoussi, Hichem ; Richard, Cédric. / Joint adaptive quantization and fading channel estimation for target tracking in wireless sensor networks. IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009. 2009. pp. 612-615
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