Research Article
Blind Source Separation for Wireless Networks: A Tool for Topology Sensing
@INPROCEEDINGS{10.1007/978-3-030-73423-7_3, author={Enrico Testi and Elia Favarelli and Andrea Giorgetti}, title={Blind Source Separation for Wireless Networks: A Tool for Topology Sensing}, proceedings={Cognitive Radio-Oriented Wireless Networks. 15th EAI International Conference, CrownCom 2020, Rome, Italy, November 25-26, 2020, Proceedings}, proceedings_a={CROWNCOM}, year={2021}, month={3}, keywords={Blind source separation Topology sensing Wireless networks Cognitive radio}, doi={10.1007/978-3-030-73423-7_3} }- Enrico Testi
Elia Favarelli
Andrea Giorgetti
Year: 2021
Blind Source Separation for Wireless Networks: A Tool for Topology Sensing
CROWNCOM
Springer
DOI: 10.1007/978-3-030-73423-7_3
Abstract
In this work, a tool for topology sensing of a non-collaborative wireless network using power profiles captured by radio-frequency (RF) sensors is proposed. Assuming that the features of the network (i.e., the number of nodes, medium access control (MAC) and routing protocols) are unknown and that the sensors observe signal mixtures because of the wireless medium, blind source separation (BSS) is used to separate the traffic profiles. Successively, the topology of the network is inferred by detecting causal relationships between the separated streams. According to the numerical results, the proposed tool senses the topology with promising accuracy when operating in mild shadowing conditions, even with a relatively low number of radio-frequency (RF) sensors.
