Deep Learning Based Spectrum Sensing for Data Transmission in WSN

Abstract

This article discusses DL-based Spectrum Sensing (SS) in Cognitive radio employing CNN-BIGRU networks for efficient data transfer. Cognitive radio is an extremely important issue in wireless communication. Radio frequency spectrum scarcity exists in wireless communication owing to the development of digital technologies. SS is critical to successfully exploiting spectrum resources. The complexity and efficiency of allocation are reduced when using traditional SS procedures. If the main user is not present, resources may be properly used for the secondary user by employing DL-based SS. The CNN-BIGRU network discussed in this article can be used for effective data transfer. Good precision can be achieved by employing this model. In addition, low SNR signals can be successfully classified and provide information on whether the channel is idle or busy.