ITITMay 7

Near-field Channel Estimation for XL-RIS-aided mmWave MIMO Systems

arXiv:2605.0671949.2
Predicted impact top 18% in IT · last 90 daysOriginality Incremental advance
AI Analysis

For mmWave communication systems using XL-RIS, this work addresses the challenging hybrid-field channel estimation problem with reduced pilot overhead.

The paper proposes a two-stage channel estimation scheme for XL-RIS-aided mmWave MIMO systems that handles near-field spherical-wave characteristics of RIS-user channels. The scheme achieves competitive estimation performance with substantially reduced pilot overhead compared to existing near-field benchmarks.

Extremely large-scale reconfigurable intelligent surfaces (XL-RISs) have emerged as a promising technology for millimeter-wave (mmWave) communications. However, the exceedingly large aperture of XL-RISs renders the RIS-user links likely to operate in the near-field region, where the conventional planar-wave assumption and angular-domain sparse representation become invalid, thus making channel estimation significantly more challenging. In this paper, we investigate cascaded channel estimation for an XL-RIS-aided multi-user multiple-input multiple-output (MU-MIMO) system, in which the BS-RIS channel is modeled in the far field, while the RIS-user channels exhibit near-field spherical-wave characteristics. To tackle the resulting hybrid-field estimation problem, we propose a low-overhead two-stage channel estimation scheme by jointly exploiting the common BS-RIS link shared by all users and the polar-domain sparsity of the RIS-user channels. Specifically, the multi-antenna users are firstly decomposed into multiple virtual single-antenna users, based on which the common BS-RIS parameters are extracted from a typical virtual user and the RIS-user channels are initialized via compensated polar-domain sparse recovery. Then, an alternating least-squares refinement procedure is developed to jointly improve the common BS-RIS operator and the user-specific RIS-side channels. Simulation results show that the proposed scheme achieves competitive channel estimation performance with substantially reduced pilot overhead compared with the existing near-field benchmarks.

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