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

Area of Science:

• Wireless Communication
• Signal Processing
• Aerospace Engineering

Background:

• Unmanned Aerial Vehicle (UAV)-assisted wireless systems utilize carrier aggregation (CA) to address bandwidth limitations.
• High-mobility UAV communication presents significant challenges for accurate channel estimation (CE) due to dynamic channel characteristics.

Purpose of the Study:

• To propose a novel line-of-sight (LoS) and echo sensing-based CE scheme for CA-enabled UAV-assisted communication systems.
• To enhance CE accuracy for both primary component carriers (PCC) and secondary component carriers (SCCs) in dynamic UAV environments.

Main Methods:

• Employed LoS sensing and echo sensing to acquire prior information for refining PCC channel estimation.
• Utilized the path-sharing property between PCC and SCCs to reconstruct SCC channels in the delay-Doppler (DD) domain.
• Implemented a three-stage process for SCC channel reconstruction.

Main Results:

• The proposed scheme significantly improves CE accuracy for both PCC and SCCs.
• Simulation results validate the effectiveness of the developed channel estimation method.
• The scheme demonstrates robustness against variations in system parameters.

Conclusions:

• The LoS and echo sensing-based CE scheme effectively addresses the challenges of channel estimation in high-mobility CA-enabled UAV systems.
• The proposed method offers a reliable solution for improving communication performance in UAV-assisted networks.