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Stochastic Transceiver Optimization in Multi-Tags Symbiotic Radio Systems

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Document pages: 13 pages

Abstract: Symbiotic radio (SR) is emerging as a spectrum- and energy-efficientcommunication paradigm for future passive Internet-of-things (IoT), where somesingle-antenna backscatter devices, referred to as Tags, are parasitic in anactive primary transmission. The primary transceiver is designed to assist bothdirect-link (DL) and backscatter-link (BL) communication. In multi-tags SRsystems, the transceiver designs become much more complicated due to thepresence of DL and inter-Tag interference, which further poses new challengesto the availability and reliability of DL and BL transmission. To overcomethese challenges, we formulate the stochastic optimization of transceiverdesign as the general network utility maximization problem (GUMP). Theresultant problem is a stochastic multiple-ratio fractional non-convex problem,and consequently challenging to solve. By leveraging some fractionalprogramming techniques, we tailor a surrogate function with the specificstructure and subsequently develop a batch stochastic parallel decomposition(BSPD) algorithm, which is shown to converge to stationary solutions of theGNUMP. Simulation results verify the effectiveness of the proposed algorithm bynumerical examples in terms of the achieved system throughput.

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