Beam Focusing for Near-Field Multi-User MIMO Communications
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Abstract (arXiv)
Large antenna arrays and high-frequency bands are two key features of future wireless communication systems. The combination of large-scale antennas with high transmission frequencies often results in the communicating devices operating in the near-field (Fresnel) region. In this paper, we study the potential of beam focusing, feasible in near-field operation, in facilitating high-rate multi-user downlink multiple-input multiple-output (MIMO) systems. As the ability to achieve beam focusing is dictated by the transmit antenna, we study near-field signaling considering different antenna structures, including fully-digital architectures, hybrid phase shifter-based precoders, and the emerging dynamic metasurface antenna (DMA) architecture for massive MIMO arrays. We first provide a mathematical model to characterize near-field wireless channels as well as the transmission pattern for the considered antenna architectures. Then, we formulate the beam focusing problem for the goal of maximizing the achievable sum-rate in multi-user networks. We propose efficient solutions based on the sum-rate maximization task for fully-digital, (phase shifters based-) hybrid and DMA architectures. Simulation results show the feasibility of the proposed beam focusing scheme for both single- and multi-user scenarios. In particular, the designed focused beams are such that users residing at the same angular direction can communicate reliably without interfering with each other, which is not achievable using conventional far-field beam steering.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 May 2021.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 1; 2025: 2; 2026: 1.
8 papers.
- 2022Near-Field Channel Estimation for Extremely Large-Scale Array Communications: A model-based deep learning approachcited by 1
- 2022Learning Optimal Phase-Shifts of Holographic Metasurface Transceiverscited by 1
- 2023AI-Empowered Hybrid MIMO Beamformingcited by 1
- 2024Near-field Beam training for Extremely Large-scale MIMO Based on Deep Learningcited by 1
- 2025Joint Transmit and Pinching Beamforming for Pinching Antenna Systems (PASS): Optimization-Based or Learning-Based?cited by 1
- 2025Near Field Localization via AI-Aided Subspace Methodscited by 1
- 2023HoloBeam: Learning Optimal Beamforming in Far-Field Holographic Metasurface Transceiverscited by 0
- 2026Near-Field Wideband Channel Estimation for XL-MIMO Systems via Denoising Diffusion Modelcited by 0
- 2026Near-Field Wideband Channel Estimation for XL-MIMO Systems via Denoising Diffusion Model22 Apr 2026
- 2025Near Field Localization via AI-Aided Subspace Methods1 Apr 2025
- 2025Joint Transmit and Pinching Beamforming for Pinching Antenna Systems (PASS): Optimization-Based or Learning-Based?12 Feb 2025
- 2024Near-field Beam training for Extremely Large-scale MIMO Based on Deep Learning5 Jun 2024
- 2023HoloBeam: Learning Optimal Beamforming in Far-Field Holographic Metasurface Transceivers30 Dec 2023
- 2023AI-Empowered Hybrid MIMO Beamforming3 Mar 2023
- 2022Learning Optimal Phase-Shifts of Holographic Metasurface Transceivers12 Dec 2022
- 2022Near-Field Channel Estimation for Extremely Large-Scale Array Communications: A model-based deep learning approach28 Nov 2022