Social Optimization and Pricing Policy in Cognitive Radio Networks with an Energy Saving Strategy

Abstract EN

The rapid growth of wireless application results in an increase in demand for spectrum resource and communication energy.

In this paper, we firstly introduce a novel energy saving strategy in cognitive radio networks (CRNs) and then propose an appropriate pricing policy for secondary user (SU) packets.

We analyze the behavior of data packets in a discrete-time single-server priority queue under multiple-vacation discipline.

With the help of a Quasi-Birth-Death (QBD) process model, we obtain the joint distribution for the number of SU packets and the state of base station (BS) via the Matrix-Geometric Solution method.

We assess the average latency of SU packets and the energy saving ratio of system.

According to a natural reward-cost structure, we study the individually optimal behavior and the socially optimal behavior of the energy saving strategy and use an optimization algorithm based on standard particle swarm optimization (SPSO) method to search the socially optimal arrival rate of SU packets.

By comparing the individually optimal behavior and the socially optimal behavior, we impose an appropriate admission fee to SU packets.

Finally, we present numerical results to show the impacts of system parameters on the system performance and the pricing policy.