Software-Defined Radio Experimental Setup for Multi-Antenna Spectrum Sensing Algorithms

Spectrum Sensing (SS) will play a pivotal role in 6G Cognitive Radio Networks (CRN), in which unlicensed users could dynamically use the spectrum and perform opportunistic transmission, while avoiding interference. In this paper, we focus on multiple-antenna SS and we compute the performance of three schemes, the Roy's Largest Root Test (RLRT), the Generalized Likelihood Ratio Test (GLRT), and the Energy Detector (ED), for different values of false alarm probability and signal-tonoise ratio, and fixed number of sensors at the secondary user receiver, equal to 4. In order to assess the performance of SS schemes in a real environment, we set up a software-defined radio (SDR) experimental testbed by using Universal Software Radio Peripherals (USRPs) for primary user signal transmission and secondary user data acquisition. Results of the SDR setup, shown in terms of Receiving Operating Characteristic (ROC) curve and performance curve, are compared against simulated data, confirm the performance superiority of RLRT over ED and GLRT also in a real environment.