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This paper investigates the optimization of the primary base station (BS) to effectively support a symbiotic radio (SR) network between a primary network consisting of a single user and the secondary network comprising multiple tags of a backscatter network. The tags use non-orthogonal multiple access for communication, and we consider passive tags and reconfigurable tags. To decode data successfully, the primary user adopts a successive interference cancellation technique. However, in practical networks, imperfect channel state information is inevitable and can significantly degrade network performance. Surprisingly, this issue has not been previously investigated. Thus, considering these factors, we aim to optimize the beamforming vectors at the BS, supporting both the primary and backscatter networks, while simultaneously maximizing the weighted sum rate or minimizing transmit power. These optimization problems are non-convex, and we develop a combination of alternative optimization, fractional programming, and semi-definite relaxation techniques for solutions. We conduct evaluations of the proposed algorithms considering both fixed and reconfigurable tags with variable reflection coefficients. Furthermore, extensive numerical simulations are presented to demonstrate the validity and performance gains achieved by the proposed schemes. The results of our study highlight the improved benefits that SR systems can offer through the utilization of our optimization schemes.

Beamforming Designs for Enabling Symbiotic BackCom Multiple Access Under Imperfect CSI