Robust DOA estimation and tracking for integrated sensing and communication massive MIMO OFDM systems

被引:6
|
作者
Xu, Kui [1 ]
Xia, Xiaochen [1 ]
Li, Chunguo [2 ]
Xie, Wei [1 ]
Liu, Jie [1 ]
Zhu, Rangang [3 ]
He, Huasen [4 ]
机构
[1] Army Engn Univ PLA, Coll Commun Engn, Nanjing 210007, Peoples R China
[2] Southeast Univ, Sch Informat Sci & Engn, Nanjing 210096, Peoples R China
[3] Natl Univ Def Technol, Sch Elect Countermeasures, Hefei 230037, Peoples R China
[4] Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230026, Peoples R China
基金
中国国家自然科学基金;
关键词
integrated sensing and communication; massive multiple input multiple output (MIMO); orthogonal frequency-division multiplexing (OFDM); direction-of-arrival (DOA) estimation and tracking; frame structure and pilot sequence; INCOHERENTLY DISTRIBUTED SOURCES; LOCALIZATION; OPTIMIZATION; MUSIC;
D O I
10.1007/s11432-022-3661-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a robust direction-of-arrival (DOA) estimation and tracking scheme for a massive multiple input multiple output (MIMO) orthogonal frequency-division multiplexing (OFDM) system using integrated sensing and communication (ISAC). First, a frame structure is designed to enable integrated DOA estimation and tracking, as well as data transmission. Then, coherent combining and multipath combining methods are proposed as pilot signal preprocessing methods for robust DOA estimation and tracking. Finally, for ISAC massive MIMO-OFDM systems, a fast Fourier transform (FFT) algorithm-based robust DOA estimator design is proposed, including a preamble-based initial DOA estimation scheme and an embedded pilot-based DOA tracking scheme. The simulation results demonstrate that the proposed robust DOA estimation and tracking method can obtain accurate DOA estimation even when the signal-to-noise ratio is low. Furthermore, the estimation performance outperforms the conventional multiple signal classification (MUSIC) and estimation of signal parameters via rotational invariance technique (ESPRIT) methods.
引用
收藏
页数:19
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