Future Internet of Things (IoT) is envisioned to provide large-scale network connections, low latency and high data rates to satisfy diverse quality of service (QoS) demands of IoT devices. In this research, we are concerned with the issue of enhancing quality of experience (QoE) for IoT devices by deploying a multi-access edge computing (MEC) caching-enabled unmanned aerial vehicle (UAV) network. Specifically, we characterize IoT devices’ QoE by mean opinion score (MOS) and intend to improve their QoE by optimizing multi-dimensional resources in terms of UAV deployment, caching placement and user association. To solve the challenging optimization problem, matching theory-based alternating iterative method is then developed. Finally, extensive simulations are designed to verify the effectiveness and advantages of the proposed algorithm.