Sequential Uniformly Reweighted Sum-Product Algorithm for Cooperative Localization in Wireless Networks
Graphical models have been widely applied in solving distributed inference problems in wireless networks. In this paper, we formulate the cooperative localization problem in a mobile network as an inference problem on a factor graph. Using a sequential schedule of message updates, a sequential unifo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-08-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/164816 |
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| Summary: | Graphical models have been widely applied in solving distributed inference problems in wireless networks. In this paper, we formulate the cooperative localization problem in a mobile network as an inference problem on a factor graph. Using a sequential schedule of message updates, a sequential uniformly reweighted sum-product algorithm (SURW-SPA) is developed for mobile localization problems. The proposed algorithm combines the distributed nature of belief propagation (BP) with the improved performance of sequential tree-reweighted message passing (TRW-S) algorithm. We apply the SURW-SPA to cooperative localization in both static and mobile networks, and evaluate its performance in terms of localization accuracy and convergence speed. |
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| ISSN: | 1550-1477 |