Rydberg Atomic Receivers for Net-Zero 6G Wireless Communication and Sensing: Progress, Experiments, and Sustainable Prospects
Abstract
Against the backdrop of the global drive to advance the green transformation of the information and communications technology (ICT) industry and leverage technological innovation to facilitate the achievement of Net-Zero carbon goals, research into Rydberg atomic receivers (RAREs) is gaining significant interest. RAREs leverage the electron transition phenomenon for signal reception, offering significant advantages over conventional radio frequency receivers in terms of miniaturized antenna design, high sensitivity, robust interference resistance, and compact form factors, which positions them as a competitive alternative for meeting zero-carbon communication demands. This article systematically elaborates on the basic principle, state-of-the-art progress, and novel experiments of RAREs in quantum wireless communication and sensing. In this first-of-its-kind work, we experimentally verify the RARE-based orthogonal frequency division multiplexing transmission and reveal the potential of deep learning design in optimizing quantum wireless systems. Finally, we delve into the prospect of integrating RARE with existing cutting-edge application scenarios, while mapping out critical pathways for developing Rydberg-based wireless systems.
Keywords
Cite
@article{arxiv.2603.21498,
title = {Rydberg Atomic Receivers for Net-Zero 6G Wireless Communication and Sensing: Progress, Experiments, and Sustainable Prospects},
author = {Yi Tao and Zhen Gao and Zhiao Zhu and De Mi and Zhonghuai Wu and Zijian Zhang and Fusang Zhang and Dezhi Zheng and Sheng Chen},
journal= {arXiv preprint arXiv:2603.21498},
year = {2026}
}
Comments
10 pages, 5 figures, IEEE journal article. This work systematically introduces Rydberg atomic receivers (RAREs) for net-zero 6G communication and sensing, including fundamental principles, state-of-the-art advances, and the first experimental verification of RARE-based OFDM signal reception and AI-driven end-to-end image transmission