LAUSR

In this paper, we investigate a novel uplink reconfigurable intelligent surface (RIS) based multi-user multi-input multi-output symbiotic radio system. It indicates that each RIS, as an Internet-of-Things (IoT) device, enhances the primary transmission from a nearby user to the base station (BS), and simultaneously transmits its own information to the BS by backscattering modulation. By embedding environmental sensors on the RISs, the proposed system enables the IoT transmission of locally collected environmental data to the BS while assisting the primary communications from the users to the BS. 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 sum-rate of both the primary and IoT transmissions. For the perfect CSI case, we propose an algorithm based on the block coordinate descent (BCD) method to solve the problem. We also propose another algorithm with a similar framework to reduce the computational complexity. 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. Furthermore, when the channel estimation error is small, the performance loss due to imperfect CSI is insignificant.