A Return and Risk Model for Efficient Spectrum Sharing in Cognitive Radio Networks

Cognitive Radio technology releases the spectrum from shackles of authorized licenses and facilitates the trading of spectrum bands. In the spectrum market, primary users (PUs) set prices for their vacant bands and sell them for monetary gains, and secondary users (SUs) buy the bands and opportunistically use them to satisfy their service demands when the PUs are not active. However, when there are multiple bands available for the SUs to access, the SU confronts the challenges of how to choose bands and how to split his traffic over them considering both the contention from peer SUs as well as the unpredictable activities of the PUs. In this paper, we propose a return and risk model to represent these concerns of the SU, and help the SU to make appropriate decisions of traffic distribution over available spectrum bands, either the bands belonging to SU itself or the bands shared with PUs. The simulation and analysis show that our spectrum sharing scheme is efficient in terms of maximum return for given risk or minimum risk for given return, and is also effective in improving the spectrum utilization and SUs' satisfactory degrees.