Probabilistic Scheme for Intelligent Jammer Localization for Wireless Sensor Networks

Yadav A.P.; Davuluri S.K.; Charan P.; Keshta I.; Gavilán J.C.O.; Dhiman G. · Lecture Notes in Networks and Systems (2023) · DOI: 10.1007/978-981-99-3177-4_33

Resumen

With the development of artificial intelligence technology, intelligent interference sources can improve the interference effect by changing their transmission power, which leads to the failure of traditional positioning technology based on received signal strength. Therefore, a sensor wake-up mechanism is introduced to study multi-interference sources based on block-compressed sensing positioning method. First, wake up the sensor nodes periodically, while improving the utilization effectiveness of the sensor nodes and the accuracy of positioning information collection; secondly, considering that the distance between the distance and the received signal strength cannot be determined when the transmission power of the interference source is unknown and changes. Then, based on the compressive sensing theory, the positioning problem is modeled as a block sparse vector reconstruction problem; finally, a variation-based algorithm is designed by exploring the law of power variation. The Wake-VBEM reconstruction algorithm based on Bayesian mean expectation accurately reconstructs the target position vector. The simulation proves that the proposed method can simultaneously realize the position estimation of multiple interference sources and effectively improve the service life of the network when the interference source power is unknown and changes.

Instituciones: Universidad Privada del Norte