Channel Estimation in UAV-Assisted OFDM Systems by Leveraging LoS and Echo Sensing with Carrier Aggregation

Unmanned aerial vehicle (UAV)-assisted wireless communication systems often employ the carrier aggregation (CA) technique to alleviate the issue of insufficient bandwidth. However, in high-mobility UAV communication scenarios, the dynamic channel characteristics pose significant challenges to channel estimation (CE). Given these challenges, integrated sensing and communication (ISAC), which combines communication and sensing functionalities, has emerged as a promising solution to enhance CE accuracy for UAV systems. Meanwhile, the dominant line-of-sight (LoS) characteristics inherent in UAV scenarios present a valuable opportunity for further exploitation. To this end, this paper proposes a LoS and echo sensing-based CE scheme for CA-enabled UAV-assisted communication systems. Firstly, LoS sensing and echo sensing techniques are employed to acquire sensing-assisted prior information. Subsequently, the obtained prior information is utilized to refine the CE of the primary component carrier (PCC) in CA, thereby improving the accuracy of channel parameter estimation for the PCC. Based on the path-sharing property between PCC and secondary component carriers (SCCs), a three-stage scheme is proposed to reconstruct the channel of SCCs. In Stages I and II, the path-sharing property is exploited to reconstruct the LoS and non-line-of-sight (NLoS) paths of the SCCs in the delay-Doppler (DD) domain, respectively. Finally, an iterative procedure is applied to enhance the initial reconstruction and further recover non-shared transmission paths between PCC and SCCs. Simulation results demonstrate that the proposed method effectively enhances the CE accuracy for both PCC and SCCs. Furthermore, the proposed scheme exhibits robustness against parameter variations.