Routing and Spectrum Decision in Single Transceiver Cognitive Radio Networks

Cognitive radio improves spectrum utilization by allowing secondary users to transmit on vacant spectrum band allocated to licensed users without affecting their activity on that spectrum. Cognitive radio address the problem of spectrum inefficiency as well as spectrum scarcity but it's quite challenging to capture the volatile spectral nature of cognitive radio environment using single transceiver. This work proposes an optimization model for combined spectrum decision and routing in single transceiver cognitive radio networks for maximizing overall network capacity. Proposed centralized algorithm ensures some minimum throughput for all flows in the network using fairness ratio and maximizes this ratio to increase the overall network capacity. Proposed model considers channel heterogeneity which is a critical aspect in making efficient spectrum decision and selects optimal route based on primary user's activity and application requirements of the cognitive users. Results show that proposed optimization model increases the overall network capacity by maximizing fairness ratio for all the flows in the network and is quite comparable with the existing multipath routing models for cognitive radio network and performs better in case of random topology.