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. 2022 Jul 8;22(14):5125.
doi: 10.3390/s22145125.

DOA Estimation in B5G/6G: Trends and Challenges

Ningjun Ruan  1   2 , Han Wang  3 , Fangqing Wen  2   4 , Junpeng Shi  5
Affiliations

DOA Estimation in B5G/6G: Trends and Challenges

Ningjun Ruan et al. Sensors (Basel). .

Abstract

Direction-of-arrival (DOA) estimation is the preliminary stage of communication, localization, and sensing. Hence, it is a canonical task for next-generation wireless communications, namely beyond 5G (B5G) or 6G communication networks. Both massive multiple-input multiple-output (MIMO) and millimeter wave (mmW) bands are emerging technologies that can be implemented to increase the spectral efficiency of an area, and a number of expectations have been placed on them for future-generation wireless communications. Meanwhile, they also create new challenges for DOA estimation, for instance, through extremely large-scale array data, the coexistence of far-field and near-field sources, mutual coupling effects, and complicated spatial-temporal signal sampling. This article discusses various open issues related to DOA estimation for B5G/6G communication networks. Moreover, some insights on current advances, including arrays, models, sampling, and algorithms, are provided. Finally, directions for future work on the development of DOA estimation are addressed.

Keywords: DOA estimation; array signal processing; massive MIMO.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Illustration of beamforming in B5G/6G wireless communication networks.
Figure 2
Figure 2
Schematic diagram of DOA-based positioning using two cooperative deciphers: (left) 2D positioning using 1D-DOA estimation; (right) 3D positioning using 2D-DOA estimation.
Figure 3
Figure 3
Illustration of near-field source and far-field source.
Figure 4
Figure 4
(a) Mutual coupling effect in DOA estimation with a ULA; (b) illustration of a coprime array; (c) EMVS array.
Figure 5
Figure 5
A general framework of a spatial CS for DOA estimation.
Figure 6
Figure 6
An example of a temporal CS for DOA estimation.
Figure 7
Figure 7
An example of a hybrid CS for DOA estimation.
See this image and copyright information in PMC

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