Cellular-Connected UAV with Adaptive Air-to-Ground Interference Cancellation and Trajectory Optimization

TL;DR

This paper proposes an adaptive interference cancellation and trajectory optimization method for cellular-connected UAVs, significantly enhancing UAV data throughput while maintaining ground user requirements.

Contribution

It introduces a joint design of interference cancellation modes, resource allocation, and UAV trajectory to maximize throughput in cellular UAV communications.

Findings

Adaptive IC improves UAV throughput by 30% over non-adaptive schemes.

Joint optimization outperforms separate design approaches.

Proposed algorithm converges efficiently with practical computational complexity.

Abstract

This letter studies a cellular-connected unmanned aerial vehicle (UAV) scenario, in which a UAV user communicates with ground base stations (GBSs) in cellular uplink by sharing the spectrum with ground users (GUs). To deal with the severe air-to-ground (A2G) co-channel interference, we consider an adaptive interference cancellation (IC) approach, in which each GBS can decode the GU's messages by adaptively switching between the modes of IC (i.e., precanceling the UAV's resultant interference) and treating interference as noise (TIN). By designing the GBSs' decoding modes, jointly with the wireless resource allocation and the UAV's trajectory control, we maximize the UAV's data-rate throughput over a finite mission period, while ensuring the minimum data-rate requirements at individual GUs. We propose an efficient algorithm to solve the throughput maximization problem by using the techniques of alternating optimization and successive convex approximation (SCA). Numerical results show that our proposed design significantly improves the UAV's throughput as compared to the benchmark schemes without the adaptive IC and/or trajectory optimization.