Research On Beamforming Algorithms Of Multi-user Symbiotic Communication Based On Reconfigurable Intelligent Surface

With the development of digitalization,enhanced devices that require increased bandwidth are increasingly adopted,and the global mobile traffic is also increasing exponentially.To overcome the challenges of high throughput and super-massive access,novel wireless communication technologies with high energy and spectrum efficiency have aroused significant attention worldwide.Recently,symbiotic radio(SR)has been regarded as one of the promising solutions to address the mentioned challenges.In an SR system,secondary transmitters,transmit their information to the corresponding receivers with the energy and spectrum resources of primary transmitters.In return,the secondary system provides multi-path diversity to the primary system,yielding mutual benefits between the two energy spectrum sharing systems.In this paper,we investigate a novel reconfigurable intelligent surface(RIS)based multi-user multi-input multi-output symbiotic radio system in two different scenarios,downlink and uplink,respectively.In the downlink scenario,each RIS,as an backscatter device,enhances the primary transmission from base station(BS)to a nearby user,and simultaneously transmits its own information to the user by backscattering modulation.By embedding environmental sensors on the RISs,the proposed system enables the Io T transmission of locally collected environmental data to the users while assisting the primary communications.For the downlink scenario,we are interested in maximizing the weighted sum-rate of both primary and Io T transmissions by jointly designing the active transmit beamforming at BS and the passive beamforming at each RIS under the maximum transmit power constraint at the BS.Based on fractional programming method and alternating optimization technique,we propose three low-complexity algorithms to tackle the problem.Compared to different benchmark schemes,simulation results demonstrate that with the aid of the RISs,the users can benefit from the enhanced primary transmission from the BS,and receive information from the associated RISs via Io T transmission.In the uplink scenario,each RIS enhances the primary transmission from a nearby user to the BS,and simultaneously transmits the collected environmental information to the BS by backscattering modulation.For the uplink scenario,we consider both the case of perfect and imperfect channel state information(CSI),and design the active beamforming at the BS and the passive beamforming at the RISs jointly to maximize the weighted sumrate of both the primary and Io T transmissions.For the perfect CSI case,we propose an algorithm based on the block coordinate descent(BCD)method to solve the problem.For the imperfect CSI case,an algorithm based on BCD and the online successive convex approximation technique is proposed.Simulation results show that the proposed system achieves significant performance gain over a number of baseline schemes for both the perfect and imperfect CSI cases.