# Channel Charting-assisted Non-orthogonal Pilot Allocation for Uplink XL-MIMO Transmission

arXiv: https://arxiv.org/abs/2412.20920 · HTML: https://mlsanity.com/paper/2412.20920/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Dec 2024.

## Built on by (most cited first, 2 of 2)

- [CSI-tuples-based 3D Channel Fingerprints Construction Assisted by MultiModal Learning](https://mlsanity.com/paper/2603.25288/) (2026)
- [NARRAS: Edge-Triggered Distributed Inference for CSI-Based Localization in Vehicular IoT Networks](https://mlsanity.com/paper/2606.11914/) (2026)

## Abstract (arXiv)

Extremely large-scale multiple-input multiple-output (XL-MIMO) is critical to future wireless networks. The substantial increase in the number of base station (BS) antennas introduces near-field propagation effects in the wireless channels, complicating channel parameter estimation and increasing pilot overhead. Channel charting (CC) has emerged as a potent unsupervised technique to effectively harness varying high-dimensional channel statistics to enable non-orthogonal pilot assignment and reduce pilot overhead. In this paper, we investigate near-field channel estimation with reduced pilot overhead by developing a CC-assisted pilot scheduling. To this end, we introduce a polar-domain codebook to capture the power distribution of near-field XL-MIMO channels. The CC-assisted approach uses such features as inputs to enable an effective low-dimensional mapping of the inherent correlation patterns in near-field user terminal (UT) channels. Building upon the mapped channel correlations, we further propose a near-field CC-assisted pilot allocation (NCC-PA) algorithm, which efficiently enhances channel orthogonality among pilot-reusing UTs. Numerical results confirm that the NCC-PA algorithm substantially elevates the wireless transmission performance, offering a marked improvement over the conventional far-field CC-PA approach.