Research Article
Sensing-Assisted Channel Estimation in ISAC Systems
@INPROCEEDINGS{10.1007/978-3-031-86203-8_7, author={Rui Yin and Yexin Shi and Wei Qi and Xianfu Chen and Celimuge Wu and Yusheng Ji}, title={Sensing-Assisted Channel Estimation in ISAC Systems}, proceedings={Wireless and Satellite Systems. 14th EAI International Conference, WiSATS 2024, Harbin, China, August 23--25, 2024, Proceedings, Part II}, proceedings_a={WISATS PART 2}, year={2025}, month={3}, keywords={Integrated sensing and communication OFDM-MIMO Artificial intelligence Channel estimation}, doi={10.1007/978-3-031-86203-8_7} }- Rui Yin
Yexin Shi
Wei Qi
Xianfu Chen
Celimuge Wu
Yusheng Ji
Year: 2025
Sensing-Assisted Channel Estimation in ISAC Systems
WISATS PART 2
Springer
DOI: 10.1007/978-3-031-86203-8_7
Abstract
In future Sixth-Generation (6G) mobile communication, satellite communication is a crucial means of extending mobile networks worldwide. However, in satellite communication systems, the transmission capacity between ground stations and users has become a bottleneck for satellite communication systems. For this issue, Integrated Sensing and Communication (ISAC) technology and Artificial Intelligence (AI), which has been widely studied, has the potential to offer excellent solutions. This paper explores a Uformer-based sensing-assisted communication system that enhances channel estimation accuracy through the design of a Uformer-based channel estimation enhancement algorithm. By formulating a global optimization problem, we seek to improve resource efficiency through finding the optimal resource allocation schemes. Initially, the system utilizes radar data to obtain reconstructed channels and employs communication data for channel estimation. The proposed neural network model then fuses these data into a new and more accurate channel state information. Finally, we present a resource allocation algorithm and validate the performance of all proposed algorithms through simulations.
