{"ID":2881217,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.13067","arxiv_id":"2508.13067","title":"Low-complexity Leakage Minimization Beamforming for Large-scale Multi-user Cell-Free Massive MIMO","abstract":"We propose a low-complexity beamforming (BF) design for information leakage minimization in multi-user (MU) cell-free massive multiple-input multiple-output (CF-mMIMO) systems. Our approach leverages fractional programming (FP) to reformulate the secrecy rate maximization problem into a tractable difference-of-convex form. To efficiently solve the resulting non-convex problem, we employ the Concave-Convex Procedure (CCP), enabling fast convergence to a local optimum. Simulation results demonstrate that the proposed scheme achieves secrecy rates comparable to state-of-the-art (SotA) methods, while significantly reducing computational complexity and improving convergence speed.","short_abstract":"We propose a low-complexity beamforming (BF) design for information leakage minimization in multi-user (MU) cell-free massive multiple-input multiple-output (CF-mMIMO) systems. Our approach leverages fractional programming (FP) to reformulate the secrecy rate maximization problem into a tractable difference-of-convex f...","url_abs":"https://arxiv.org/abs/2508.13067","url_pdf":"https://arxiv.org/pdf/2508.13067v2","authors":"[\"Iván Alexander Morales Sandoval\",\"Getuar Rexhepi\",\"Kengo Ando\",\"Giuseppe Thadeu Freitas de Abreu\"]","published":"2025-08-18T16:41:28Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}