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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xianren Wu Zhi Tian |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Michigan Technol. Univ., Houghton, MI (Xianren Wu; Zhi Tian) |
| Abstract | This paper considers the problem of decentralized data fusion (DDF) for large wireless sensor networks with stringent bandwidth requirements. To reduce the power and bandwidth costs of wireless transmissions, each sensor node is confined to quantize its sensing data and send 1-bit information only. Under this setting, we derive the maximum likelihood (ML) data fusion rule for decentralized parameter estimation, and analyze its Cramer-Rao lower bound (CRLB) of the fusion performance in the sense of mean square distortion. Depending on the underlying noise characteristics, our 1-bit DDF scheme can achieve estimation performance competitive to or even surprisingly better than that of centralized fusion over unquantized data. There is considerable saving in communication costs, which in turn reduces network energy consumption. Furthermore, we investigate network optimization, for which a worst-case robust design methodology is adopted to formulate a well-behaved min/max optimization problem. From the information processing viewpoint, the resulting optimized network offers robust fusion performance at minimal costs of communication resources |
| Sponsorship | The Inst. of Electr. and Electron. Eng., Inc. Circuits and Syst. Soc. (IEEE CASS) |
| File Size | 211268 |
| File Format | |
| ISBN | 142440469X |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2006.1661068 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-05-14 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Constraint optimization Bandwidth Sensor fusion Wireless sensor networks Costs Maximum likelihood estimation Design optimization Parameter estimation Performance analysis Energy consumption sensor networks decentralized data fusion distributed signal processing CRLB network optimization |
| Content Type | Text |
| Resource Type | Article |
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