Desired Signal Power Maximization With Interference Alignment for RIS Aided MIMO Interference Network

The multi-user multiple-input multiple-output interference channel assisted by reconfigurable intelligent surface (RIS) is considered. We jointly optimize the precoding and decoding matrices as well as RIS discrete parameters, to maximize the desired signal power with interference alignment (IA) conditions. The interference leakage is penalized to the objective function by the Courant penalty technique. This simplifies the optimization problem and tackles the possible infeasibility. In the new objective function, the desired signal power maximization and the interference leakage minimization are combined together. We propose two efficient strategies to update the penalty parameter, namely the constraint violation update and the total signal to total interference plus noise ratio (TSTINR) update. The variables are updated alternatively, with either Schur decompositions or projected gradient inner updates. Simulations show that the proposed model greatly improves the benchmark model in terms of the achieved sum rate with less computational cost.