Secure resource allocation against colluding eavesdropping in a user-centric cell-free massive multiple-input multiple-output system

We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive eavesdroppers. To address the problem of limited pilot resources, a scheme is proposed to allocate the pilot with the minimum pollution to users based on access point selection and optimize the pilot transmission power to improve the accuracy of channel estimation. Aiming at the secure transmission problem under a colluding eavesdropping environment by multiple passive eavesdroppers, based on the local partial zero-forcing precoding scheme, a transmission power optimization scheme is formulated to maximize the system’s minimum security spectral efficiency. Simulation results show that the proposed scheme can effectively reduce channel estimation error and improve system security.