题    目：Upper and Lower Bound Sum Rate Approximation for RIS Aided MIMO Interference Network

主讲人：王凯民  讲师

单    位：河南科技大学

时    间：2026年7月2日  10:00

地    点：郑州校区九章学堂南楼C座209

摘    要：Reconfigurable intelligent surface (RIS) has emerged as a prospective technology, capable of shaping radio wave propagation and enhancing performance gains. The RIS aided multiple input multiple output interference channel is considered. We aim to maximize the sum rate by jointly optimizing the precoding matrices and RIS parameters, subject to the transmit power constraints. Both upper and lower bound sum rate approximation schemes are designed for this nonconvex problem. First, for the upper bound approximation, the minimax problem is formulated through the approximated Lagrangian function, where the precoding matrices are determined by the RIS matrix and the Lagrange multiplier, and are eliminated in the problem. A single loop primal dual algorithm is proposed. In each iteration, the RIS parameter and the Lagrange multiplier are updated by one projected gradient step and quadratic interpolation, respectively. Its complexity only grows linearly in the number of RIS elements. In addition, the total signal to total interference plus noise ratio is introduced for the sum rate lower bound approximation. The fractional objective function is reformulated via the Dinkelbach’s technique, and the variables are updated with closed form through alternating optimization and projected gradient method. Simulations show that the upper bound approach performs well with only 10% computational time of the compared methods, and shows high efficiency in one-iteration test; the lower bound approach achieves almost the highest sum rate using little computational cost.

简    介：王凯民，现为河南科技大学数学与统计学院讲师，2025年6月获北京邮电大学博士学位，研究方向为非线性最优化理论及其在无线通信中的应用，曾获北京运筹学会青年优秀论文奖。主要成果在Journal of Global Optimization, Optimization, IEEE Transactions on Communications等期刊上发表。