Title | Compressed sensing of Gauss-Markov random field with wireless sensor networks |
Publication Type | Conference Paper |
Year of Publication | 2008 |
Authors | Oka, A., and L. Lampe |
Conference Name | Sensor Array and Multichannel Signal Processing Workshop, 2008. SAM 2008. 5th IEEE |
Pagination | 257 -260 |
Date Published | jul. |
Keywords | a-priori statistical information, channel coding, compressed sensing, fusion center, Gauss-Markov random fields, Gaussian processes, intersensor communication, Markov processes, matrix algebra, matrix sensing, random processes, reconstruction algorithms, sensor arrays, sensor fusion, sensors array, statistical analysis, statistical model, wireless sensor networks |
Abstract | We propose a scalable and energy efficient method for reconstructing a dasiasparsepsila Gauss-Markov random field that is observed by an array of sensors and described over wireless channels to a fusion center. The encoder is universal, i.e. invariant to the statistical model of the source and the channel, and is based on compressed sensing. The reconstruction algorithms exploit the a-priori statistical information about the field and the channel at the fusion center to yield a performance comparable to information theoretic bounds. Furthermore, by putting stringent constraints on the sensing matrix we avoid (or even eliminate) inter-sensor communication while suffering negligible degradation in performance. |
URL | http://dx.doi.org/10.1109/SAM.2008.4606867 |
DOI | 10.1109/SAM.2008.4606867 |