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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Thanou, D. Kokiopoulou, E. Pu, Y. Frossard, P. |
| Copyright Year | 1991 |
| Abstract | We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. We propose a novel quantization scheme that exploits the increasing correlation between the values exchanged by the sensors throughout the iterations of the consensus algorithm. A low complexity, uniform quantizer is implemented in each sensor, and refined quantization is achieved by progressively reducing the quantization intervals during the convergence of the consensus algorithm. We propose a recurrence relation for computing the quantization parameters that depend on the network topology and the communication rate. We further show that the recurrence relation can lead to a simple exponential model for the quantization step size over the iterations, whose parameters can be computed a priori. Finally, simulation results demonstrate the effectiveness of the progressive quantization scheme that leads to the consensus solution even at low communication rate. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 194 |
| Ending Page | 205 |
| Page Count | 12 |
| File Size | 2650105 |
| File Format | |
| ISSN | 1053587X |
| Volume Number | 61 |
| Issue Number | 1 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Quantization Convergence Noise Signal processing algorithms Algorithm design and analysis Correlation Network topology sensor networks Distributed average consensus progressive quantization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering |
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