Sparse Estimation for XL-MIMO with Unified LoS/NLoS Representation

Autor:	Shi, Xu, Wang, Xuehan, Tan, Jingbo, Wang, Jintao
Rok vydání:	2024
Předmět:	Computer Science - Information Theory Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	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. Comment: ICC 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.12506 Zobrazit plný text záznamu View this record from Arxiv