This paper studies a cell-free (CF) massive multi-input multi-output (MIMO) simultaneous wireless information and power transmission (SWIPT) system and proposes a user-centric (UC) access point (AP) selection method and a trade-off performance optimization scheme for spectral efficiency and energy efficiency. In this system, users have both energy harvesting and information transmission functions, and according to the difference between energy harvesting and information transmission, a flexible AP selection scheme is designed. This paper analyses the trade-off between energy efficiency and spectral efficiency, proposes an evaluation index that takes into account both energy efficiency and spectral efficiency, and jointly optimizes the AP selection scheme and the uplink (UL) and downlink (DL) time switching ratio to maximize the trade-off performance. Then, the non-convex problem is converted to a geometric planning (GP) problem to solve. The simulation results show that by implementing a suitable AP selection scheme and UL and DL time allocation, the information processing scheme on the AP side has a slight loss in spectral efficiency, but the energy efficiency is close to the performance of global processing on the central processing unit (CPU).

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This paper presents the application of intelligent reflecting surfaces (IRSs) in a cell-free massive MIMO network to enhance secure transmission in the system. Multiantenna access points (APs) need to transmit information to users safely and reliably via IRSs without fully knowing the channel state information (CSI) of a multiantenna eavesdropper (Eve) or the accurate beamforming information of a jammer. Specifically, through joint optimization of the AP active beamforming (ABF) and IRS passive beamforming (PBF), the information leaked to the Eve is limited by a set threshold, and restrictions on the IRS reflection phase are considered to maximize the weighted sum rate of the system’s downlink transmission. To solve this multivariate-coupled nonconvex problem, we propose a joint precoding framework under imperfect CSI, using the generalized S-procedure, fractional programming (FP), and multidimensional complex quadratic transformation (MCQT) to transform the original complex nonconvex problem into an easily solvable convex optimization problem, and an alternating algorithm to obtain the optimal solution for precoding and IRS phase shifting. Simulation results show that the proposed scheme can significantly increase the weighted sum rate of the system compared to conventional antijamming methods while revealing that the scheme is effective in enhancing secure system transmission.