Sum Rate Maximization of Full-Duplex MIMO Monostatic Backscatter Networks Under Residual Self-Interference

Backscatter communication (BCS) devices have low cost, low power, and the ability to harvest energy, enabling ultra-green Internet of things (IoT) networks with energy autonomy. However, they achieve only low data rates and a limited communication range. A monostatic backscatter (MBS) network of multiple tags with a full-duplex (FD) multiple-input multiple-output (MIMO) reader is subject to self-interference (SI), which exacerbates the aforementioned problems. Since SI cannot be removed ideally, the residual SI (RSI) degrades the system performance. Thus, the main goal of this study is to correct this problem. To this end, we formulate the maximization of the sum rate by optimizing the precoder and combiner filters of the reader and the reflection coefficients of the tags. The constraints are to limit the effects of the RSI and allow the energy harvested by the tags to exceed a minimum. Because the problem is nonconvex, we utilize alternating optimization (AO) to split it into three subproblems and develop iterative algorithms. The simulation results validate and quantify the achievable sum rate.