Spectrum Sensing based on Energy Detection for Cognitive Radio Using Poission Traffic (International Journal of Psychosocial Rehabilitation, 2020)
Cognitive Radio Network could be a style of communication wherever licensed bands of the first users area are created and offered to the secondary user with constrained interference to the PUS. Cognitive radio is taken into thought as a novel paradigm of coming up with wireless communication structures that have objectives at enhancing the spectrum utilization. Spectrum sensing is one of the foremost, very important factors in cognitive radio networks. Among those algorithms, Poisson traffic-based energy detection has been extensively employed in follow due to its process and implementation simplicity. Throughput maximization is one of the most important challenges in cognitive radio networks. During this paper, eventualities of output maximization are analyzed that are thought of as primary user protection and thought of as packet collision. Just in case of element protection, output may be maximized by choosing either an acceptable variety of secondary users, an acceptable sensing time, or an acceptable fusion rule at the fusion center. Just in case of packet collision, optimum frame length is chosen to maximize the output. The simulation results verify that output may be increased by choosing the correct sensing time, correct range of creature genus, correct fusion rule, and correct frame period.