Secure symbol-level precoding for reconfigurable intelligent surface-aided cell-free networks

With the improvement in communication network density, inter-cell interference has become severe. Due to the blurring of boundaries, cell-free networks are considered as a solution. However, it faces some challenges, such as high energy consumption due to the deployment of a large number of base stations, and security issues in complex communication scenarios. To tackle these issues, we propose a novel modeling scheme involving symbol-level precoding and reconfigurable intelligent surfaces (RIS). This solution can reduce the base station transmission power while ensuring communication layer security. Then, we decompose the non-convex problem of modeling into two sub-problems and solve them iteratively. The first sub-problem is to design symbol-level precoding which can be realized by an efficient gradient descent algorithm. The second sub-problem is about solving the reflection coefficients of RIS, which can be obtained by a Riemann conjugate gradient algorithm. In simulations, our proposed method outperforms benchmark methods. While ensuring physical layer security, the power consumption of cell-free networks has been reduced by 6 dBm.