NOMA-Assisted Symbiotic Backscatter: Novel Beamforming Designs Under Imperfect SIC

TL;DR

This paper develops novel beamforming strategies for NOMA-assisted symbiotic networks with imperfect SIC, enhancing primary user data rates and energy harvesting while addressing non-convex optimization challenges.

Contribution

It introduces two optimal beamforming algorithms for NOMA symbiotic networks under imperfect SIC, using advanced optimization techniques and providing extensive performance validation.

Findings

Digital beamforming increases harvested power by 2,160%

Data rate improves by 314.5% with proposed schemes

Significant performance gains over random beamforming

Abstract

Optimal beamforming designs under imperfect successive interference cancellation (SIC) decoding for a symbiotic network of non-orthogonal multiple access (NOMA) primary users and a secondary ambient tag have been lacking. We address that issue here. The primary base station (BS) serves NOMA users and a passive tag simultaneously in this network. We develop two transmit beamforming designs to meet the user and tag requirements while mitigating the effect of imperfect SIC. Specifically, we design optimal BS transmit beamforming and power allocation to either maximize the weighted sum rate of NOMA users and the tag or minimize the BS transmit power under the minimum rate requirements while satisfying the tag minimum energy requirement. Because both these problems are non-convex, we propose algorithms using alternative optimization, fractional programming, and semi-definite relaxation techniques. We also analyze their computational complexity. Finally, we present extensive numerical results to validate the proposed schemes and to show significant performance gains while keeping the tag design intact. For example, the proposed digital beamforming increases the harvested power and data rate by 2.16e3 % and 314.5 % compared to random beamforming.