Throughput maximization problem for random allocation of channels in a cognitive radio network

Abstract

In this paper, throughput analysis is presented for random allocation of channels in a cognitive radio network. In random allocation, each primary user dynamically and randomly selects a channel in each time slot. Secondary users are able to dynamically detect the idle channels in each time slot and compete to access these channels. We develop a model for throughput of primary and secondary users. A Poisson probability law is utilized for secondary users for throughput computation. The parameters such as traffic generation probability, fraction of primary users are computed for quantification of throughput. Some specified number of primary and secondary users are utilized in the analysis in light of maximum throughput.

Unified Channel Management for Cognitive Radio Sensor Networks Aided Internet of Things

“…By stability, we mean how smoothly IoT devices conduct communication during frame f without interruption from the 5G user. The authors of [ 28 , 29 ] introduce a dynamic channel selection scheme (DCSS) and dynamic random channel selection scheme (DRCSS) to optimize the throughput. Several OSR schemes [ 30 , 31 , 32 ] have been proposed in the literature for QoS provisioning.…”