Joint reflection coefficient, time proportion and power allocation for multicarrier backscatter communications

Massive growth of Internet of Things (IoT) applications is anticipated to result in an inevitable increase in network energy consumption (EC). To address this concern, we tackle the energy efficiency (EE) maximization problem for the multicarrier wireless-powered backscatter communication networks (WPBCNs), by jointly optimizing the resource allocation (RA) of transmit power, reflection coefficient (RC), and time proportion, under the worst-case scenario with interference between multiple backscatter devices in the multicarrier WPBCNs. To solve this problem, we propose an adaptive nonlinear fractional programming (NLFP)-based time-power swarm optimization (ANT-PSO) scheme, which is specifically designed to circumvent the hardness of the NLFP problem (NLFPP), as well as the randomness in the channel gains and interference present in the network. We apply the NLFP transformation method to improve the tractability of the problem. Additionally, we develop a new joint RC, time proportion and transmit power optimization algorithm based on swarm intelligence, with additional functions designed according to energy causality and resource constraints to facilitate solution exploration within the feasible range. Simulation results show that our proposed scheme outperforms several baseline schemes in the average worst-case EE for scenarios with different maximum transmit power levels, numbers of backscatter links and numbers of subcarriers.