A Contract-Based Incentive Mechanism in RF-Powered Backscatter Cognitive Radio Networks

Radio frequency (RF) powered cognitive radio networks (CRNs) integrated with ambient backscatter technology is a newborn communication scheme. However, the time allocation is still an important issue that limits the performance of this system seriously. Unlike the centralized distribution methods under complete information in previous studies, in this paper, we introduce a financing contract mechanism to solve the time allocation problem with strongly incomplete information, where the primary user (PU) only knows the probability distribution of each secondary transmitter's (ST's) type. In this contract, the PU and SUs act as the seller and buyers, respectively. The mutually beneficial relationships between the PU and SUs can be linked with the signed contract about the amount of the signal transmitting time and the payment. Then, we discuss three cases where either or both adverse selection and moral hazard are present due to the information asymmetry. Moreover, the optimal contracts under three scenarios are further formulated and solved by using the Lagrangian multiplier method. Finally, simulation results show that compared with the case of complete information the contract with adverse selection and moral hazard has a small performance loss, which is acceptable on account of the practical superiority of the strongly incomplete information case.