Unmanned Aerial Vehicles (UAVs) have been successfully employed in cooperative tasks over recent years, particularly in the applications for smart cities. In such scenario, a networked control system (NCS) framework is usually adopted since measurement and actuation data are mainly transmitted through communication networks. This paper proposes an integrated control architecture for a Cloud-based fixed-wing UAV system, where the control logic resides in the Cloud and sensing and actuating signals are transmitted over a realistic wireless network. The proposed control strategy leverages model predictive control (MPC) and a specialized Kalman filter in combination with two ad-hoc buffers, which enables simultaneous compensation for measurement and control input packet dropouts. Simulations of a nonlinear aircraft model show the effectiveness and advantages of proposed integrated scheme over an existing linear quadratic (LQ)-based control strategy.