Low-Complexity Receiver Beamforming Design for RIS-Aided ISCC Systems with Computational Offloading Management

This paper investigates the data reception, radar sensing, and computational offloading of a reconfigurable intelligent surface (RIS)-assisted integrated sensing, communication, and computation (ISCC) system under spectrum sharing and computational offloading constraints. By jointly optimizing the receiver beamformings and RIS phase shifts, an effective trade-off between radar sensing and communication energy consumption is achieved, thereby minimizing the total system energy consumption. To address the complex coupling and non-convex nature of the optimization variables, we propose a hybrid optimization framework in which the receiver beamforming design is tackled via a double minorize-maximization alternating direction penalty method design (DMMADPM), while the RIS phase shifts are optimized using a successive approximation element-wise block coordinate descent design (SAEBCD). Simulation results demonstrate that the proposed algorithm converges rapidly and outperforms baseline schemes in suppressing interference across time, frequency, spatial, and energy domains. It also enables flexible trade-offs among radar sensing, communication, and computation performance under channel estimation error, providing a robust receiver beamforming design for next-generation ISCC networks in resource-constrained environments.