On RF-OAM Tx-Rx Directional Misalignment and Its Deep Learning Based Correction

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On RF-OAM Tx-Rx Directional Misalignment and Its Deep Learning Based Correction
Title:
On RF-OAM Tx-Rx Directional Misalignment and Its Deep Learning Based Correction
Journal Title:
2025 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting (AP-S/CNC-USNC-URSI)
Keywords:
Publication Date:
02 January 2026
Citation:
Ma, Y., & Shin, F. C. P. (2025). On RF-OAM Tx-Rx Directional Misalignment and Its Deep Learning Based Correction. 2025 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting (AP-S/CNC-USNC-URSI), 2963–2966. https://doi.org/10.1109/ap-s/cnc-usnc-ursi55537.2025.11266050
Abstract:
Orbital angular momentum (OAM) electromagnetic (EM) waves offer a promising path to increased spectrum efficiency by enabling multiplexing beyond traditional time, frequency, and space division methods. However, effective OAM multiplexing hinges on good alignment between transmitter (Tx) and receiver (Rx), which is challenging in radio frequency (RF). This paper quantitatively assesses the impact of Tx-Rx misalignment on RF-OAM detection and multiplexing, demonstrating the critical need for accurate alignment. We propose a deep learning (DL)-based solution for misalignment correction, of which numerical results show to be both fast and accurate.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the National Research Foundation, Singapore and Infocomm Media Development Authority - Future Communications Research Development Programme
Grant Reference no. : NA
Description:
© 2026 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
ISSN:
1947-1491
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