Increasing Power Efficiency of Spatial Cognitive Radio System by Sectorization Technique

In this study, we examine a Cognitive Radio (CR) network comprising a Primary User (PU) and Secondary Users (SUs), all of whom are equipped with multiple antennas to take advantage of spatial characteristics for transmission. The SUs cooperate to analyze the PU’s beam of transmission, dividing the available space between the PU and the SUs. Instead of activating all SUs, we propose a sectorization technique to limit the number of active SUs. This is achieved by identifying the dominant sectors through weighted power estimates. Our study evaluates the accuracy of beam estimation and sector selection using metrics such as angular false and missed detections, the percentage of false and missed activations, and the percentage of sectorization failure. The results indicate that the sectorization technique enhances the system power efficiency by allowing a lower number of active users to achieve better beamwidth estimation accuracy, compared to using all SUs. Additionally, our sector selection process successfully identifies the dominant sectors even when the beam spans multiple sectors. We also investigate the influencing parameters impacting the selection accuracy, such as the number of sensing units per sector, the number of sectors, and the beamwidth of the PU’s signal.