Abstract

Cognitive radio spectrum is traditionally divided into two spaces. Black space is reserved to primary users transmissions and secondary users are able to transmit in white space. To get more capacity, black space has been divided into black and grey spaces. Grey space includes interfering signals coming from primary and other secondary users, so the need for interference suppression has grown. Novel applications like Internet of Things generate narrowband interfering signals. In this paper, the performance of the forward consecutive mean excision algorithm (FCME) method is studied in the presence of narrowband interfering signals. In addition, the extension of the FCME method called the localization algorithm based on double-thresholding (LAD) method that uses three thresholds is proposed to be used for both narrowband interference suppression and intended signal detection. Both Long Term Evolution (LTE) signal simulations and real-world LTE and Wireless Local Area Network (WLAN) signal measurements were used to verify the usability of the methods in future cognitive radio applications.