Oct 15, 2019 · In this paper we look into the wireless spectrum anomaly detection problem for crowdsourced sensors. We first analyze in detail the nature of ...

Mar 13, 2019 · Abstract—Automated wireless spectrum monitoring across frequency, time and space will be essential for many future applications.

We conduct extensive experiments based on a large-scale crowdsourced network dataset with five million samples. The dataset involves round trip time (RTT) ...

Jun 19, 2020 · Electrosense+ allows users to remotely decode specific parts of the radio spectrum. It builds on the centralized architecture of its predecessor, Electrosense.

This model achieves an average anomaly detection accuracy above 80% at a constant false alram rate of 1% along with anomaly localization in an unsupervised ...

Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features; Crowdsourced wireless spectrum anomaly detection. Adapted from: https://github ...

Apr 1, 2020 · The main idea of the proposed research is to engage community users (radios) to detect misuse, and identify and punish unruly devices. By ...

Jun 13, 2019 · The pros and cons of the newly proposed crowdsourced spectrum monitoring, anomaly detection and signal classification models will be covered ...

These algorithms provide statistics on spectrum usage, collaborative spectrum data decod- ing, help in applications like anomaly detection and localization.

Nov 21, 2018 · This system monitors transmissions in real-time and generates alarm events when detecting anomalous transmitters, which can trigger further ...