Game-based approach of fair resource allocation in wireless powered cooperative cognitive radio networks

Abstract

A resource allocation approach is proposed for wireless powered cooperative cognitive radio network (WP-CCRN) in this paper, where multiple secondary users (SUs) capture both the wireless energy and the authorized spectrum from primary user (PU) to communicate with a secondary access point (SAP). In return, SUs serve as relay nodes to help the primary transmitter (PT) forwarding data to the primary receiver (PR). For the sake of the stable cooperation between PU and SUs, we present a game-based fair resource allocation algorithm (GFRAA) that takes into account the utilities of both sides. The Stackelberg game is applied for solving the resource allocation problem between PU and SUs, where PU acts as a leader while SUs are followers. To solve the non-convex optimization problem in the primary network, a new variable namely allocated energy is introduced to transform the primal problem into a convex problem. Meanwhile, the relationship among SUs is modeled as a Supermodular game. Since SUs are rational and selfish, a fairness evaluation mechanism is designed to adjust the fairness among SUs. Simulation results unveil the trade-off between the fairness of SUs, the throughput of PU, and the sum-throughput of SUs. The superiority of the GFRAA has been validated by comparing with the other two algorithms.