# A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications
## 3 Overview of Previous Studies on IRS-Assisted UAV Communications
### Improvement of Energy Efficiency  
Energy efficiency is a crucial factor for the implementation of all systems. For wireless communications systems, in particular, the energy efficiency exerts a significant effect on the system performance and device size. Therefore, the energy efficiency is accepted as one of the most fundamental and important performance criteria, together with the spectral efficiency. In this subsection, we introduce the research trends of the IRS-assisted UAV communications systems from the perspective of energy efficiency. Table 2 briefly summarizes the main features of the previous works relevant to the improvement of energy efficiency. Reference [68] investigated how to maximize the received power of the ground users using a single UAV and multiple IRSs. It was shown that the energy efficiency of such systems is highly dependent on the number of elements in the IRS. Reference [69] aimed to minimize UAV power consumption using a decaying deep Q-network (D-DQN), which was devised based on the deep Q-network (DQN) algorithm with the concept of a decaying learning rate. Furthermore, the proposed algorithm was used to compare the performance of orthogonal multiple access and NOMA systems. The authors of [70] maximized the energy efficiency of a multicell uplink system with the help of an aerial BS, i.e., a UAV-mounted IRS. The proposed system was shown to significantly improve the energy efficiency compared to a conventional system with amplify-and-forward relays in UAVs, especially when the optimal transmit power and a large number of reflective elements were implemented. Similarly, Refs. [70; 71; 72] aimed to maximize the energy efficiency of the IRS-assisted UAV communications systems. The system proposed in [71] provides communication and computing services to the ground terminals by operating UAVs as mobile edge computing (MEC) servers in the air. However, UAVs should operate in an adverse environment where UAV-to-ground links are frequently blocked by ground obstacles, which may result in the long latency of tasks. To address this issue, it is essential to configure the IRS so that the propagation channels between the UAV and ground terminals are improved. As a result, Reference [71] showed that IRS-assisted UAVs have great potential for improving the performance of MEC, as well as pure wireless communications. To improve the secrecy energy efficiency in an IRS-assisted UAV system with eavesdroppers, the authors of [72] argued for the need for the optimization of the IRS phase shift, UAV trajectory, user association, and transmit power. The authors of [73] considered a resource allocation strategy and the UAV trajectory and velocity in an alternating algorithm that was proposed to minimize the average total power consumption of the system. Reference [74] aimed to improve UAV connectivity and energy efficiency by maximizing the number of available devices during the activation period and verified the possibility of maximizing service performance with large-sized IRSs. An optimization approach that minimizes the weighted total energy consumption of vehicles with transmit power constraints and aerial road side units was proposed in [75]. Specifically, an IRS network was devised, and the efficiency of the optimized dual-IRS-enabled radio transmission was boosted by using time-slot scheduling and task allocation. Reference [76] aimed to minimize the transmit power of UAVs through UAV placement, IRS phase shift, user association, and IRS association adjustment. To reduce the total power consumption of all