Sparse Estimation for XL-MIMO with Unified LoS/NLoS Representation
<|reference_start|>Sparse Estimation for XL-MIMO with Unified LoS/NLoS Representation: Extremely large-scale antenna array (ELAA) is promising as one of the key ingredients for the sixth generation (6G) of wireless communications. The electromagnetic propagation of spherical wavefronts introduces an additional distance-dependent dimension beyond conventional beamspace. In this paper, we first present one concise closed-form channel formulation for extremely large-scale multiple-input multiple-output (XL-MIMO). All line-of-sight (LoS) and non-line-of-sight (NLoS) paths, far-field and near-field scenarios, and XL-MIMO and XL-MISO channels are unified under the framework, where additional Vandermonde windowing matrix is exclusively considered for LoS path. Under this framework, we further propose one low-complexity unified LoS/NLoS orthogonal matching pursuit (XL-UOMP) algorithm for XL-MIMO channel estimation. The simulation results demonstrate the superiority of the proposed algorithm on both estimation accuracy and pilot consumption.<|reference_end|>
@article{shi2024sparse,
    title={Sparse Estimation for XL-MIMO with Unified LoS/NLoS Representation},
    author={Xu Shi, Xuehan Wang, Jingbo Tan, Jintao Wang},
    journal={arXiv preprint arXiv:2403.12506},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.12506},
    primaryClass={cs.IT eess.SP math.IT}
}