Abstract

This paper introduces a new spatial domain-based self-interference cancellation (SIC) precoding method named constrained minimum mean square error (C-MMSE) for an asymmetric massive multiple-input multiple-output (mMIMO) full-duplex (FD) system. The main idea is to translate the commonly used singular value decomposition (SVD)-based null-space projection approach, which is unfeasible in our considered system model, into an optimization problem under MMSE criterion, where additional constraints are implemented to perform SIC. Theoretical derivation of the C-MMSE precoder is presented, followed by performance comparison with conventional MMSE precoding, where no constraints are added for SIC. We theoretically show that the C-MMSE scheme outperforms the conventional one in terms of SIC, and allows the FD system to work under an almost interference-free environment. Additionally, we also assess the performance of the proposed method under imperfect channel state information (CSI), to further evaluate the robustness of our spatial precoder in more realistic conditions. We show that the C-MMSE precoder outperforms MMSE in terms of interference suppression ratio (ISR), even in CSI imperfection. Additionally, the C-MMSE achieves the same spectral efficiency (SE) as an hypothetical perfect SIC in a wide SNR range, whereas the MMSE is upper bounded in large SNR range.