With the continuous development of wireless communication and antenna technologies, directional antenna-based UAV ad hoc networks have been increasingly applied to various scenarios, such as battlefields, disaster relief, and other extreme situations. At present, directional UAV ad hoc networks face an imbalance in multi-dimensional resource allocation, including time slots, frequency, and power. To address this problem, a communication protocol based on the Multi-Frequency Time Division Multiple Access (MF-TDMA) framework is designed for UAV ad hoc networks. This protocol takes into account the interference caused by antenna sidelobes and time-frequency resource reuse, while balancing the link priority and fairness issues brought by simultaneous connections of different nodes.A hybrid iterative decomposition algorithm combining the Whale Optimization Algorithm (WOA) and Successive Convex Approximation (SCA) is proposed to solve the multi-dimensional resource optimization problem. Simulation results show that the proposed algorithm effectively improves network performance and resource utilization while ensuring the quality of service (QoS) requirements for high-priority links under the premise of fast convergence.