Characterization of Near-Field Sub-Regions for Phased-Array Antennas: A Comprehensive Study

Core Concepts

This paper provides a comprehensive characterization of three key near-field sub-regions for phased-array antennas: the Fraunhofer region, the radial-focal region, and the non-radiating region, highlighting the unique challenges and opportunities presented by near-field signal propagation in emerging wireless technologies like 6G.

Abstract

• Bibliographic Information: Monemi, M., Bahrami, S., Rasti, M., & Latva-aho, M. (2024). A Study on Characterization of Near-Field Sub-Regions For Phased-Array Antennas. arXiv preprint arXiv:2411.02425v1.
• Research Objective: This paper aims to provide a comprehensive and categorized study of various electromagnetic propagation regions in the near-field of phased-array antennas, focusing on three key boundaries: the Fraunhofer distance, the radial focal distance, and the non-radiative distance.
• Methodology: The authors revisit existing definitions of near-field boundaries and perform detailed calculations to characterize each boundary for phased array antennas. They derive closed-form expressions wherever possible and validate their findings through full-wave simulations using HFSS software.
• Key Findings:
  • The study reveals that the commonly used Fraunhofer distance for phased arrays, derived for on-boresight scenarios, is not valid for off-boresight scenarios. The authors derive a closed-form expression for the Fraunhofer distance for phased arrays considering various angles between the principal axis and the boresight.
  • The authors highlight the inaccuracies of characterizing the radial focal point using the simplified uniform spherical wave (USW) channel model. They propose a practical algorithm to achieve accurate radial beamfocusing at the desired location, considering the non-uniform spherical wave (NUSW) model.
  • The study clarifies misconceptions about the non-radiating and Fresnel distances, demonstrating that the non-radiating distance is consistently lower than half a wavelength for various phased array configurations.
• Main Conclusions: The paper provides a more generalized perspective for characterizing near-field sub-regions for phased-array antennas, considering off-boresight scenarios and more realistic channel models. The findings have significant implications for designing and optimizing near-field communication systems, particularly in the context of emerging technologies like 6G that utilize ELAAs and operate at very high frequencies.
• Significance: This research contributes significantly to the understanding and characterization of near-field propagation for phased-array antennas, which is crucial for the development of next-generation wireless communication systems.
• Limitations and Future Research: The study primarily focuses on Line-of-Sight (LoS) scenarios. Future research could explore the characterization of near-field sub-regions in the presence of obstacles and multipath propagation. Additionally, investigating the impact of different antenna element types and array geometries on the near-field characteristics would be beneficial.

Stats

The on-boresight Fraunhofer distance is dF0 = 2D²/λ, where D is the maximum dimension of the antenna and λ is the wavelength.
For off-boresight scenarios, the Fraunhofer distance for phased arrays is increased about 4 times when compared to the on-boresight scenario.
For a 5-element ULA with half-wavelength inter-element spacing (D = 2λ), the upper bound of phase error resulting from simplified calculations is 0.2%.
Increasing the height of a phased array antenna from zero (on-boresight) to 35 cm can increase the maximum near-field coverage distance from 183 m to 731 m for a carrier frequency of 28 GHz and an aperture dimension of 0.7 × 0.7 m².
The non-radiating distance (dNR) for various phased array configurations is consistently lower than half a wavelength.

Quotes

Key Insights Distilled From

A Study on Characterization of Near-Field Sub-Regions For Phased-Array Antennas

by Mehdi Monemi... at arxiv.org 11-06-2024

https://arxiv.org/pdf/2411.02425.pdf

Deeper Inquiries

How will the characterization of near-field sub-regions be affected in non-line-of-sight (NLoS) scenarios with multipath propagation?

Answer:
In non-line-of-sight (NLoS) scenarios with multipath propagation, the characterization of near-field sub-regions becomes significantly more complex compared to the simplified Line-of-Sight (LoS) case. Here's how:

Fraunhofer Distance: The concept of Fraunhofer distance, based on a single direct path and planar wavefront approximation, becomes less accurate. Multipath reflections and scattering lead to multiple wavefronts arriving at the receiver with varying delays and angles. This makes the transition from near-field to far-field less distinct and potentially dependent on the specific multipath environment.

Radial Focal Distance: The radial focal distance, relying on precise phase control for constructive interference at a specific point, is severely impacted. Multipath components introduce interference patterns that distort the intended focal point. Achieving a sharp, well-defined focal point in a rich scattering environment becomes extremely challenging.

Non-Radiating Distance: While the basic principle of reactive fields dominating near the antenna still holds, the presence of reflecting surfaces and scattering objects in NLoS scenarios can alter the distribution of reactive power. This might lead to variations in the non-radiating distance compared to free-space calculations.
Key Challenges in NLoS Near-Field Characterization:

Channel Modeling: Accurate channel models that capture the complexities of near-field multipath propagation are crucial. These models need to account for path loss, delay spread, angular spread, and potentially polarization effects.
Beamforming and Focusing: Traditional beamforming techniques designed for far-field or simple near-field models become inadequate. Advanced algorithms that consider the multipath channel and potentially exploit the spatial diversity offered by the near-field are required.
Measurement and Characterization: Experimental characterization of near-field sub-regions in realistic NLoS environments is essential. This involves developing measurement setups and techniques to accurately capture the spatial variations of the channel.

Could the proposed algorithm for radial beamforming be adapted for different array geometries, such as cylindrical or spherical arrays?

Answer:
Yes, the proposed algorithm for radial beamforming, which aims to compensate for the radial focal gap, can potentially be adapted for different array geometries like cylindrical or spherical arrays. However, modifications and considerations are necessary:

Coordinate System: The algorithm, initially formulated for planar or linear arrays using Cartesian or cylindrical coordinates, needs to be transformed to the appropriate coordinate system of the array. For cylindrical arrays, this would involve cylindrical coordinates, while spherical arrays would require spherical coordinates.

Array Factor Calculation: The array factor, representing the combined radiation pattern of the array elements, needs to be derived specifically for the new geometry. This involves considering the element positions and relative phases in the chosen coordinate system.

Radial Distance Calculation: The calculation of the radial distance between each antenna element and the desired focal point, crucial for determining the appropriate phase shifts, needs to be adjusted based on the array geometry.
Adaptation for Cylindrical Arrays:

Relatively straightforward adaptation as the cylindrical geometry maintains a constant radius in one dimension.
Modifications mainly involve expressing element positions and calculating distances in cylindrical coordinates.
Adaptation for Spherical Arrays:

More complex adaptation due to the varying radial distances of elements from the desired focal point.
Requires careful consideration of spherical coordinate transformations and distance calculations.
Additional Considerations:

Mutual Coupling: The impact of mutual coupling between antenna elements might be different for various array geometries and needs to be accounted for in the algorithm.
Computational Complexity: The computational complexity of the algorithm might increase for more complex geometries, requiring optimization strategies.

How can the understanding of near-field antenna behavior be leveraged to develop novel applications beyond traditional communication systems, such as near-field imaging or sensing?

Answer:
The unique characteristics of near-field antenna behavior, such as spatially varying phase and amplitude, offer exciting opportunities for novel applications beyond traditional communication systems. Here are some promising avenues:
Near-Field Imaging:

Higher Resolution: Near-field imaging techniques can achieve sub-wavelength resolution, surpassing the diffraction limit of conventional far-field imaging. This is because evanescent waves, carrying high spatial frequency information, are significant in the near-field.
3D Imaging: By exploiting the radial dimension information available in the near-field, 3D imaging of objects becomes feasible. This has applications in medical imaging, non-destructive testing, and material characterization.
Microwave and Millimeter-Wave Imaging: Near-field techniques are particularly relevant at higher frequencies (mmWave, THz) where achieving high resolution with far-field methods is challenging. This enables applications like security screening, medical diagnostics, and material inspection.
Near-Field Sensing:

High Sensitivity: The strong interaction of near-fields with objects enables highly sensitive sensing applications. This is valuable for detecting small changes in material properties, displacement, or presence of objects.
Short-Range Localization: Precise localization and tracking of objects in close proximity to the antenna array are possible using near-field characteristics. This has applications in robotics, indoor navigation, and gesture recognition.
Wireless Power Transfer: Efficient wireless power transfer over short distances can be achieved by exploiting the high energy concentration in the near-field. This is relevant for powering implants, sensors, and mobile devices.
Other Applications:

Near-Field Microscopy: Combining near-field principles with microscopy techniques enables imaging with nanoscale resolution, revealing details inaccessible to conventional optical microscopes.
Holographic Communications: Near-field holographic surfaces can shape and steer electromagnetic waves in complex ways, enabling high-capacity, secure communication links.
Key Enabling Technologies:

Phased Arrays: Large-scale phased arrays with precise phase and amplitude control are essential for generating and manipulating near-fields effectively.
Advanced Signal Processing: Sophisticated signal processing algorithms are crucial for extracting information from the complex near-field signals and compensating for distortions.
Computational Electromagnetics: Accurate simulations and modeling tools are necessary for designing and optimizing near-field systems.