Abstract
This paper studies distributed range-based localization in arbitrarily deployed wireless ad hoc networks. Existing range-based localization approaches depend on specially deployed anchors or require dense network deployment. Our algorithm is a distributed paradigm that only requires local information of each node. Therefore, it is applicable to the resource-limited embedded sensors. Specifically, our algorithm performs a three-stage optimization through coarse-grained, middle-grained, and fine-grained levels. We designed an efficient but accurate neural network to learn the hidden relations between the distances of nodes and their positions. Simulations show that our proposed algorithm works in many more types of network deployments than the existing approaches. Furthermore, our algorithm achieves the highest localization accuracy on average.
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Gao, R., Yang, Z., Wu, H. (2019). A Lightweight Neural Network Localization Algorithm for Structureless Wireless Sensor Networks. In: Guo, S., Liu, K., Chen, C., Huang, H. (eds) Wireless Sensor Networks. CWSN 2019. Communications in Computer and Information Science, vol 1101. Springer, Singapore. https://doi.org/10.1007/978-981-15-1785-3_21
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DOI: https://doi.org/10.1007/978-981-15-1785-3_21
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