Spectrum heterogeneity-based efficient spectrum sensing in 6G wireless communication using ATRC-LSNN and F-ExpoTIS

Abstract

Nowadays, wireless communication plays an indispensable role in people's lives. To enhance communication efficiency, accurate and timely spectrum sensing is crucial. However, the existing models were ineffective due to the dynamic characteristics of the wireless channel. Therefore, this article proposes a spectrum heterogeneity-based efficient spectrum sensing in 6G wireless communication using ATRC-LSNN and F-ExpoTIS. The RF signals are primarily gathered and then subjected to L(D)₂TSO-based optimal beamforming. Subsequently, the maximum ratio combiner and level differencing are done, followed by signal pre-processing. Thereafter, the HKSLC is established to group the signal regarding frequency. Also, the frequency bands are extracted from the grouped signal via F-ExpoTIS. Similarly, the features are extracted from the grouped signal. Now, the features and frequency bands are inputted to the ATRC-LSNN, where the spectrum is sensed. Lastly, the WT is introduced to detect the signal interferences. Thus, the experimental outcomes showed that the proposed approach had higher prominence with 97.06% accuracy.