Abstract

TLOUYAMMA, J.  and  VELEMPINI, M.. Investigative analysis of channel selection algorithms in cooperative spectrum sensing in cognitive radio networks. SAIEE ARJ [online]. 2021, vol.112, n.1, pp.4-14. ISSN 1991-1696.

The proliferation of wireless mobile devices has led to a number of challenges in mobile data communication. The world is experiencing an increasing usage of finite spectrum bands for social media and other data communication services. It is due to this high usage that the Federal Communications Commission (FCC) sought to open up some spectrum bands to be used opportunistically by secondary users (SUs). However, the coexistence of Primary Users (PUs) and SUs may cause interference which leads to wastage of spectrum resources. This study investigates the impact of interferences between PUs and SUs. To ensure higher detection of PU signal, a cooperative rule was used to decide which SU to share and make a final decision about the availability of the spectrum band. To maximize the throughput of SU, a maximum likelihood function was designed to reduce delays in searching for the next available channel for data transmission. To discover more transmission opportunities and ensuring that a good number of free channels are detected, a parallel sensing technique was employed. Matlab was used to simulate and generate the results in a distributed cognitive radio environment. The proposed extended generalized predictive channel selection algorithm (EXGPCSA) outperformed other schemes in literature in terms of throughput, service time and probability of detection.

Keywords : Cognitive radio network; cooperative sensing; parallel sensing; inter-sensing.

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