Low-complexity Leakage Minimization Beamforming for Large-scale Multi-user Cell-Free Massive MIMO
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912587104387072 |
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| author | Sandoval, Iván Alexander Morales Rexhepi, Getuar Ando, Kengo de Abreu, Giuseppe Thadeu Freitas |
| author_facet | Sandoval, Iván Alexander Morales Rexhepi, Getuar Ando, Kengo de Abreu, Giuseppe Thadeu Freitas |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_13067 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Low-complexity Leakage Minimization Beamforming for Large-scale Multi-user Cell-Free Massive MIMO Sandoval, Iván Alexander Morales Rexhepi, Getuar Ando, Kengo de Abreu, Giuseppe Thadeu Freitas Signal Processing 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. |
| title | Low-complexity Leakage Minimization Beamforming for Large-scale Multi-user Cell-Free Massive MIMO |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2508.13067 |