Beamforming Design for NOMA-Assisted Symbiotic Backscatter

Abstract

Optimal beamforming design is developed for a nonorthogonal multiple access (NOMA)-aided symbiotic radio (SR) system where a base station (BS) simultaneously serves multiple NOMA users and a secondary ambient tag. The nearest user of the tag decodes its own data and the tag data using the successive interference cancellation (SIC) technique. We design optimal transmit beamforming and power allocation at the BS to maximize the weighted sum rate of NOMA users and the tag, under the minimum rate requirements while satisfying the tag's minimum energy requirement. Because the problem is nonconvex, we propose algorithms using alternative optimization and fractional programming techniques. Our results reveal that significant performance gains can be achieved while keeping the tag design intact. For example, the proposed beamforming can increase harvested power and data rate by 2.16×10 ³ % and 314.5% compared to random beamforming.