Near-Field Communications: A Tutorial Review
Not on the map. Why?
Abstract (arXiv)
Extremely large-scale antenna arrays, tremendously high frequencies, and new types of antennas are three clear trends in multi-antenna technology for supporting the sixth-generation (6G) networks. To properly account for the new characteristics introduced by these three trends in communication system design, the near-field spherical-wave propagation model needs to be used, which differs from the classical far-field planar-wave one. As such, near-field communication (NFC) will become essential in 6G networks. In this tutorial, we cover three key aspects of NFC. 1) Channel Modelling: We commence by reviewing near-field spherical-wave-based channel models for spatially-discrete (SPD) antennas. Then, uniform spherical wave (USW) and non-uniform spherical wave (NUSW) models are discussed. Subsequently, we introduce a general near-field channel model for SPD antennas and a Green's function-based channel model for continuous-aperture (CAP) antennas. 2) Beamfocusing and Antenna Architectures: We highlight the properties of near-field beamfocusing and discuss NFC antenna architectures for both SPD and CAP antennas. Moreover, the basic principles of near-field beam training are introduced. 3) Performance Analysis: Finally, we provide a comprehensive performance analysis framework for NFC. For near-field line-of-sight channels, the received signal-to-noise ratio and power-scaling law are derived. For statistical near-field multipath channels, a general analytical framework is proposed, based on which analytical expressions for the outage probability, ergodic channel capacity, and ergodic mutual information are obtained. Finally, for each aspect, topics for future research are discussed.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 May 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 3; 2025: 1; 2026: 1.
5 papers.
- 2024A Survey on Integrated Sensing, Communication, and Computationcited by 12
- 2024Near-field Beam training for Extremely Large-scale MIMO Based on Deep Learningcited by 1
- 2024Near-Field Spot Beamfocusing: A Correlation-Aware Transfer Learning Approachcited by 0
- 2025Physics-Informed Parametric Bandits for Beam Alignment in mmWave Communicationscited by 0
- 2026Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSICcited by 0
- 2026Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSIC8 Sep 2026
- 2025Physics-Informed Parametric Bandits for Beam Alignment in mmWave Communications21 Oct 2025
- 2024A Survey on Integrated Sensing, Communication, and Computation15 Aug 2024
- 2024Near-field Beam training for Extremely Large-scale MIMO Based on Deep Learning5 Jun 2024
- 2024Near-Field Spot Beamfocusing: A Correlation-Aware Transfer Learning Approach21 May 2024