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Driven by the limited radio spectrum resources and the high energy consumption of wireless devices, symbiotic radio (SR) has recently been proposed to support passive Internet-of-Things (IoT) networks, where a primary transmitter (PT) transmits information to a primary reader (PR), while passive backscatter devices (BDs) modulate their own information on the received primary signal and backscatter the modulated signal to the same PR by adjusting their reflection coefficients. Existing works on SR have mainly studied the case of a single BD while without considering the BD's energy harvesting (EH) ability. In this paper, we aim to maximize the energy efficiency (EE) of an SR system that includes multiple BDs each being able to harvest energy while backscattering, by jointly optimizing the PT transmission power and the BDs' reflection coefficients and time division multiple access (TDMA) time slot durations for both the parasitic SR (PSR) and commensal SR (CSR) cases. To solve the formulated non-convex optimization problems, we propose a Dinkelbach-based iterative algorithm that builds on the block coordinated decent (BCD) method and the successive convex programming (SCP) technique. Simulation results show that the proposed algorithm converges fast, and the system EE is maximized when the BD that can provide the highest EE is allocated the maximum allowed time for backscattering while guaranteeing the throughput requirements for both the primary link and the other backscatter links.

Energy Efficiency Maximization for Symbiotic Radio Networks With Multiple Backscatter Devices