A Low-Complexity Sensing-Aided Timing Synchronization Method for UAV-Assisted OFDM Systems

The timing synchronization (TS) methods based on compressed sensing (CS) and machine learning (ML) in unmanned aerial vehicle (UAV)-assisted orthogonal frequency division multiplexing (OFDM) systems need to further enhance their TS correctness while also reducing computational complexity, due to the impact of time-frequency double-selective channel. To tackle this challenge, inspired by integrated sensing and communication (ISAC), a sensing-aided TS method is proposed for UAV-assisted OFDM systems. This method leverages the received echo signals at the ground base station (gBS) to establish a metric detection threshold for determining the number of resolvable paths. By leveraging the identified number, the identification of the inter-symbol interference (ISI)-free region is iteratively refined, featuring a low computational complexity. With the reduced computational complexity, simulation results indicate that compared to CS and ML-based TS methods, the proposed method significantly reduces the TS error probability and exhibits its robustness against parameter variations.