Optimizing Full-Duplex Multi-Hop UAV Networks: A Joint Approach for Positioning and Beamforming

As a key component of next-generation wireless networks, unmanned aerial vehicles (UAVs) have demonstrated significant potential in enhancing communication performance through flexible deployment and robust line-of-sight (LoS) channels. Existing studies primarily focus on single-hop or dual-hop UAV systems, neglecting the challenges of co-channel interference in multi-hop networks. This paper proposes a novel joint optimization framework for position deployment and beamforming in full-duplex multi-hop MIMO UAV relay networks. Specifically, we consider decode-and-forward (DF) relay UAVs equipped with uniform planar arrays (UPAs) to mitigate interference caused by sidelobe leakage while improving directional beam gains. To maximize the end-to-end transmission rate, we formulate a non-convex optimization problem that jointly optimizes UAV positions and transceiver beamforming matrices. The problem is decomposed into two subproblems: 1) beamforming optimization via fractional programming and 2) UAV position deployment using a customized sparrow search algorithm (SSA) with adaptive global-local search balancing. Simulation results demonstrate that the proposed algorithm significantly improves the minimum signal-to-interference-plus-noise ratio (SINR) and achieves convergence under varying UAV numbers and antenna configurations. Compared to baseline methods, the algorithm enhances spatial resolution through optimized beamforming, enabling compact UAV deployment to reduce path loss while suppressing interference.