Distributed estimation based on observations prediction in wireless sensor networks
Type
ArticleKAUST Department
Communication Theory LabComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Date
2015-03-11Online Publication Date
2015-03-11Print Publication Date
2015-10Permanent link to this record
http://hdl.handle.net/10754/564200
Metadata
Show full item recordAbstract
We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.Citation
Bouchoucha, T., Ahmed, M. F. A., Al-Naffouri, T. Y., & Alouini, M.-S. (2015). Distributed Estimation Based on Observations Prediction in Wireless Sensor Networks. IEEE Signal Processing Letters, 22(10), 1530–1533. doi:10.1109/lsp.2015.2411852Sponsors
This work was supported by the King Abdulaziz City of Science and Technology (KACST) under Grant AT-34-345. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Vincenzo Matta.Journal
IEEE Signal Processing Lettersae974a485f413a2113503eed53cd6c53
10.1109/LSP.2015.2411852