Stackelberg Game for Cognitive Ambient Backscatter Network With Perfect and Imperfect Spectrum Sensing

The combination of cognitive radio and ambient backscatter communication can effectively improve spectrum utilization and reduce power consumption. However, when multiple backscatter devices coexist in this network, the competition among secondary backscatter users (SBUs) and conflict of interest in licensed bands due to spectrum sharing are issues that cannot be ignored. In this paper, we study the Stackelberg game to achieve a win-win transmission between primary users (PUs) and SBUs in the sensing-based cognitive ambient backscatter network. The sensing-based dual bandwidth pricing mechanisms under perfect spectrum sensing and imperfect spectrum sensing are proposed, respectively. For the perfect spectrum sensing scenario, resource allocation optimization algorithms based on the Stackelberg game are formulated to maximize the bandwidth revenue of primary users and the throughput utility function of SBUs. For the imperfect spectrum sensing scenario, hybrid transmission modes and the interference to legacy links based on different detection results are considered. Furthermore, the non-convex optimization problem based on the Stackelberg game is solved in closed-form expressions by corresponding theoretical derivation. Simulation results show that the proposed pricing mechanisms can effectively improve the revenue of primary users and the throughput performance of SBUs.