Unified Near-Field Channel Modeling and Channel Parameter Estimation for ELAA

CHEN Chongbin; SUN Jian; CHANG Hengtai; ZHANG Wensheng; WANG Chengxiang

doi:10.11999/JEIT260911

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CHEN Chongbin, SUN Jian, CHANG Hengtai, ZHANG Wensheng, WANG Chengxiang. Unified Near-Field Channel Modeling and Channel Parameter Estimation for ELAA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260911

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CHEN Chongbin, SUN Jian, CHANG Hengtai, ZHANG Wensheng, WANG Chengxiang. Unified Near-Field Channel Modeling and Channel Parameter Estimation for ELAA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260911

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Unified Near-Field Channel Modeling and Channel Parameter Estimation for ELAA

doi: 10.11999/JEIT260911 cstr: 32379.14.JEIT260911

CHEN Chongbin^{1, 2
,},
SUN Jian^{1, 2
,
,},
CHANG Hengtai^{1, 2
,},
ZHANG Wensheng^{1, 2
,},
WANG Chengxiang^{3, 4
,}

1.
School of Information Science and Engineering, Shandong University, Qingdao 266237, China
2.
Shandong Provincial Key Laboratory of Intelligent Communications and Sensing-Computing Integration, Jinan 250100, China
3.
School of Information Science and Engineering, Southeast University, Nanjing 211189, China
4.
Purple Mountain Laboratories, Nanjing 211111, China

Funds: The National Natural Science Foundation of China (U24A20212), The National Key Research and Development Program of China (2022YFF0604900, 2022YFF0604903), The Research Fund of National Mobile Communications Research Laboratory, Southeast University (2025A05)

Received Date: 2026-07-02
Accepted Date: 2026-11-05
Rev Recd Date: 2026-09-04

Available Online: 2026-11-14

Abstract

Abstract

Objective As sixth-generation (6G) mobile communication systems evolve toward extremely large aperture array (ELAA) systems, conventional far-field channel models based on the plane-wave assumption become inadequate for characterizing near-field propagation. In near-field regions, electromagnetic waves exhibit spherical-wave behavior, and a strong coupling between angular and distance parameters significantly degrades the performance of existing far-field channel modeling and estimation methods. Moreover, existing near-field models are typically limited to point-scattering spherical-wave propagation based on first- and last-bouncing mechanisms, or to end-to-end spherical-wave (E2ESW) models derived from geometric optics, in which non-line-of-sight (NLoS) paths are approximated as line-of-sight (LoS) links between virtual sources and the array. However, unified channel models and high-precision parameter estimation methods for such complex propagation environments remain insufficiently developed. Methods The study considers near-field multipath propagation environments under ELAA conditions and provides a unified representation of complex propagation scenarios involving both point scattering and planar reflection, thereby improving the physical consistency of near-field channel modeling. Furthermore, to address the three-dimensional angle–distance coupling problem in uniform planar arrays (UPAs), a polar-domain sparse representation of the channel is adopted. A polar-domain simultaneous iterative gridless weighted algorithm for UPAs (P-SIGW-UPA) is used to estimate channel parameters. In addition, path types are classified by differences in spherical-wave radius and propagation distance. Results and Discussions The simulation results verify the effectiveness of the proposed unified channel model and P-SIGW-UPA algorithm. The model-mismatch analysis shows that forcing all NLoS paths to follow either the last-bouncing scatterer (LBS) or E2ESW representation introduces noticeable structural errors in mixed point-scattering and specular-reflection environments. Such mismatch increases with array aperture and decreases with propagation distance, demonstrating the necessity of unified modeling for large-aperture ELAAs (Fig. 6). The normalized mean square error (NMSE) comparisons versus propagation distance and signal-to-noise ratio (SNR) show that angular-domain methods degrade in the near field because distance-dependent wavefront curvature is neglected. In contrast, P-SIGW-UPA jointly refines angular and distance parameters in the continuous domain and achieves the best overall NMSE performance. As the channel approaches the far-field regime, the performance gap between angular- and polar-domain methods narrows, while P-SIGW-UPA remains stable (Figs. 7–9). P-SIGW-UPA also exhibits good robustness to different propagation-power configurations. Increasing the point-scattering power factor $ \beta $ slightly degrades angular-domain methods, whereas polar-domain methods remain comparatively stable. P-SIGW-UPA maintains the best NMSE over $ K=-5 $ to $ 20 $ dB, indicating robustness to different LoS/NLoS power ratios (Figs. 10 and 11). The proposed path classification method effectively distinguishes point-scattering and specular-reflection paths. The classification accuracy increases from about 43% at $ -10 $ dB SNR to about 99% at 0 dB and approaches 100% above $ 5 $ dB (Figs. 12 and 13). With increasing antenna number, P-SIGW-UPA benefits from richer spatial observations and continuous angle–distance refinement, while angular-domain methods increasingly suffer from near-field model mismatch (Fig. 14). Conclusions The main contributions of this study are summarized as follows: (1) A unified near-field spherical-wave channel model is developed for environments with coexisting point scattering and specular reflection. By integrating point-scattering and E2ESW models, the physical consistency and representation capability of near-field multipath channels are improved. (2) The P-SIGW-UPA algorithm is applied to the developed unified channel model to verify its applicability in scenarios involving both point scattering and specular reflections. Furthermore, the impact of different propagation mechanisms on parameter estimation performance is systematically investigated. (3) A joint path classification method based on distance deviation is proposed to improve the identification accuracy of different propagation mechanisms, supporting further environment sensing and channel modeling.

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