Abstract
With the popularization of wireless networks, the role of machine intelligence is becoming more and more important, where the core is that the network needs to make its own decisions through learning. Topology sensing is a fundamental issue in the field of network intellectualization, but most of the related existing studies have focused on wired networks, while the characteristics of wireless networks are relatively few investigated. In this paper, a wireless channel-oriented topology sensing method based on Hawkes process modeling is proposed for the wireless network with symmetrical connectivity. Simulation are carried out to demonstrate that how to combine wireless channel with Hawkes process and how to further process the results to improve performance.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Liu, Z., Sun, J., Shen, F., Ding, G., Wu, Q. (2019). Topology Sensing in Wireless Networks by Leveraging Symmetrical Connectivity. In: Zhai, X., Chen, B., Zhu, K. (eds) Machine Learning and Intelligent Communications. MLICOM 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-32388-2_5
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DOI: https://doi.org/10.1007/978-3-030-32388-2_5
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