Sum-Rate Maximization and Leakage Minimization for Multi-User Cell-Free Massive MIMO Systems

Cell-free massive multiple-input multiple-output (CF-mMIMO) technology seeks to enable wireless connectivity with high-rates, flexibility and scalability, by distributing the antennas of the system among multiple access points (APs), allowing the spatial degrees-of-freedom (DoF) of the system to be fully exploited. The distributed nature of CF-mMIMO systems also raises, however, a security challenge, because messages intended to a given user may be opportunistically eavesdropped by other users of the systems, leaking potentially private information. As a step towards addressing this issue, we consider the problem of beamforming (BF) design that maximize the downlink (DL) secrecy rate of the CF-mMIMO system, considering that existing approaches have shortcomings including rate performance degradation, limitations to point-to-point (P2P) and/or multiple-input single-output (MISO) scenarios, and/or poor scalability, all of which contradict the aforementioned goals of CF-mMIMO technology. With that in mind, our focus is on scalable solutions to the problem, in a manner that does not sacrifice rate or scalability. To that end, we propose an improved and accelerated power-optimizing fractional programming (FP)-based sumrate maximization (SRM)-BF, and provide an accompanying semidefinite programm (SDP)-based secrecymaximization beamforming (SecBF) which can be used to optimize the previous’ SRM-BF towards higher aggregate secrecy rates.Acomplexity analysis and comparisons via simulation demonstrate that the proposed FP-based SRM-BF outperforms the state-of-the-art (SotA), and that the SDP-based SecBF convergences quickly from the latter BF state yielding superior secrecy without significant losses in communication rate.