Frequency-Diverse Antenna With Convolutional Neural Networks for Direction-of-Arrival Estimation in Terahertz Communications

• Published in: IEEE transactions on terahertz science and technology 2024-05, Vol.14 (3), p.354-363
• Main Authors: Li, Mingxiang Stephen, Abdullah, Mariam, He, Jiayuan, Wang, Ke, Fumeaux, Christophe, Withayachumnankul, Withawat
• Format: Article
• Language: English
• Subjects: Antenna radiation patterns; Antennas; Artificial neural networks; Convolutional neural networks; Convolutional neural networks (CNNs); Direction of arrival; direction-of-arrival (DoA) estimation; Direction-of-arrival estimation; Estimation; Frequency estimation; frequency-diverse antenna; Lenses; Line of sight communication; Machine learning; machine learning (ML); Neural networks; Radiation; Signal transmission; Terahertz communications; Terahertz frequencies; Wireless communications
• ISSN: 2156-342X; 2156-3446
• DOI: 10.1109/TTHZ.2024.3358735

The IEEE 802.15.3d standard for point-to-point wireless terahertz communications is defined to support high-capacity channels. By nature, terahertz signal transmission requires line-of-sight propagation and terahertz communications operates within a challenging power budget limitation. Therefore, accurate and efficient direction-of-arrival (DoA) estimation for maximizing received power becomes paramount to achieve reliable terahertz communications. In this article, we present a frequency-diverse antenna with a machine-learning-based approach utilizing convolutional neural networks (CNNs) to estimate DoA in the terahertz communications band. The antenna is deliberately designed to break symmetry, generating quasi-random radiation patterns, while the CNN captures the relationship between the radiation patterns and their respective angles of arrival. Based on experiments, the DoA estimation results converge to a minimum validation mean squared error of 3.9^\circ and root mean squared error of 1.9^\circ. The estimation efficacy is further substantiated by a consistent performance demonstrated across diverse scenarios, encompassing various obstacles and absorbers around the propagation path. The proposed DoA estimation method shows considerable advantages as a compact, integrable, and cost-effective solution for practical terahertz communications.