To support super-massive access for future wireless communications, in this paper, we propose a novel large intelligent surface/antennas (LISA)-assisted symbiotic radio (SR) system in which a LISA, operating as an Internet-of-Things (IoT) device, transmits messages to an IoT receiver (IR) by using reflecting radio technique, and at the same time, it assists the primary transmission from a base station (BS) to a primary receiver (PR) by intelligently reconfiguring the wireless environment. We are interested in the joint design for active transmit beamforming at BS and passive reflecting beamforming at LISA to minimize the total transmit power at BS, subject to the signal-to-noise-ratio (SNR) constraint for the IoT communication and the rate constraint for the primary transmission. Due to the non-convexity of the formulated problem, for the general case, we decouple the original optimization problem into a series of subproblems using the alternating optimization method and solve them one by one based on KarushKuhnTucker (KKT) conditions and projection method. For the special case in which the direct links from BS to PR and IR are blocked, we decouple the formulated optimization problem into two subproblems, one of which is a semi-definite program (SDP) problem and the other is solved by using semi-definite relaxation (SDR) technique. The convergence performance and the computational complexity of the proposed algorithms are analyzed for both cases. Finally, simulation results are presented to validate the effectiveness of the proposed algorithms and the superiority of the proposed system.
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