RIS-Aided Interference Subspace Alignment for K -User MIMO Interference Networks

As a promising interference management technology, interference alignment (IA) applied in reconfigurable intelligent surface (RIS)-aided interference networks can eliminate the mutual interference and improve system performance. Most of existing works study the iterative RIS-aided IA schemes with high computational complexity. In this letter, we study the closed-form IA design problem for sum-rate improvement and interference mitigation, in active RIS-aided multiuser multiple-input multiple-output (MIMO) networks. A novel joint active and passive beamforming scheme based on interference subspace alignment (ISA) is proposed, where the former is to eliminate the interference completely, and the latter is to compress the interference subspace. The proposed scheme can achieve the full MIMO multiplexing gain. Simulation results show that the proposed scheme outperforms state-of-the-art benchmarks in terms of sum-rate performance and computational complexity, and the computational complexity is 15 times lower compared to the iterative RIS-aided IA scheme.