Secure Transmission Based on Access Point Classification in Cell-Free Networks

Cell-free (CF) networks are promising for solving the inter-cell interference and switching problems resulting from ultra-dense small cell deployments. This paper considers a downlink secure transmission scenario, in which the information is exposed to active eavesdroppers. A new access points (APs) classification-based transmission scheme is presented to enhance the system performance by strategically assigning different roles to the APs in CF networks. Specifically, the APs serving user equipments (UEs) are classified into service APs (SAPs) responsible for communication, and noisy APs (NAPs) responsible for defending confidential signals by emitting artificial noise. By designing beamforming and artificial noise vectors separately, we aim to maximize the secrecy sum rate while suppressing information extraction for eavesdroppers. We apply semidefinite programming and Lagrangian duals to decouple the nonconvex optimization problems, and hence, resulting in tractable formulations. The suboptimal solution is finally obtained via eigenvalue decomposition with Gaussian randomization. Numerical results demonstrate that the suboptimal solution can closely approach the optimal counterpart, and the proposed transmission scheme is advantageous in terms of secrecy rate performance compared to the state-of-the-art.