Throughput Maximization for Hybrid Backscatter Assisted Cognitive Wireless Powered Radio Networks

In this paper, we consider a cognitive wireless powered communication network for Internet of Things applications, which consists of a primary communication pair and a secondary communication system. We propose a novel hybrid harvest-then-transmit (HTT) and backscatter communication (BackCom) mode for the information transmission of the secondary communication system. When the primary channel is busy, cognitive users (CUs) backscatter the incident signal from the primary transmitter to the information receiver in the ambient backscatter (AB) mode or harvest energy for the future information transmission. When the primary channel is idle, CUs backscatter the incident signal from the power beacon in the bistatic scatter (BS) mode or work in the HTT mode to transmit information. We further investigate the optimal time allocation between the AB mode and energy harvesting and that between the BS mode and the HTT mode for the sake of maximizing the throughput of the secondary communication system, and derive the numerical solutions. To be specific, we derive the closed-form optimal solution for a single CU case, and moreover, obtain the optimal combination of the working modes. Numerical results demonstrate the advantage of our proposed hybrid HTT and BackCom mode over the benchmark mode in terms of system throughput.