SDR implementation of wideband spectrum sensing using machine learning
Zeghdoud Sabrina,
Tanougast Camel,
Teguig Djamal
et al.
Abstract:SummaryNew cognitive radio (CR) systems require high throughput and bandwidth. Hence, CR users need to detect wide frequency bands of the radio spectrum to exploit unused frequency channels. This paper proposes a new wideband spectrum sensing (WBSS) detection approach based on machine learning (ML) for scanning subchannels. The originality of the proposed approach is to detect spectrum opportunities using a narrowband spectrum sensing (NBSS) method‐based support vector machine (SVM) classification and two feat… Show more
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