Performance Analysis of a 2D-MUSIC Algorithm for Parametric Near-Field Channel Estimation

作     者：Gurgunoglu, Doga Kosasih, Alva Ramezani, Parisa Demir, Ozlem Tugfe Bjornson, Emil Fodor, Gabor 

作者机构：KTH Royal Inst Technol Sch Elect Engn & Comp Sci S-10044 Stockholm Sweden TOBB ETU Dept Elect Elect Engn TR-06560 Ankara Turkiye Ericsson Res AB Wireless Access Networks SE-16480 Stockholm Sweden 

出 版 物：《IEEE WIRELESS COMMUNICATIONS LETTERS》 (IEEE Wireless Commun. Lett.)

年 卷 期：2025年第14卷第5期

页      面：1496-1500页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：EU Horizon 2020 MSCA-ITNMETAWIRELESS Swedish Research Council [2019-05068] The 6G-MUSICAL EU project 

主　　题：Channel estimation Antennas Vectors Multiple signal classification Aperture antennas Parametric statistics Lower bound Covariance matrices Azimuth Approximation algorithms Radiative near-field aperture antennas MUSIC channel estimation Cram & eacute r-Rao lower bound 

摘      要：In this letter, we address parametric channel estimation in a multi-user multiple-input multiple-output system within the radiative near-field of the base station array with aperture antennas. We investigate a two-dimensional multiple signal classification algorithm (2D-MUSIC) to estimate both the range and the azimuth angles of arrival for the users channels, utilizing parametric radiative near-field channel models. We analyze the performance of the algorithm by deriving the Cram & eacute;r-Rao bound (CRB) for parametric estimation, and its effectiveness is compared against the least squares estimator, which is a non-parametric estimator. Numerical results indicate that the 2D-MUSIC algorithm outperforms the least squares estimator. Furthermore, the results demonstrate that the performance of 2D-MUSIC achieves the parametric channel estimation CRB, which shows that the algorithm is asymptotically consistent.