# A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications
## 3 Overview of Previous Studies on IRS-Assisted UAV Communications
### Improvement of Spectral Efficiency
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Objective** & **Design Variables** & **Scenario** \\ \hline
[58] & Maximize sum rate &
\begin{tabular}{c} UAV trajectory, \\ IRS configuration, \\ uploading power control \\ \end{tabular} & (c) \\ \hline
[59] & Maximize sum rate &
\begin{tabular}{c} 3D placement, \\ transmit power of UAVs, \\ decoding orders among users \\ \end{tabular} & (a) \\ \hline
[60] & \
\begin{tabular}{c} Maximize the rate of the strong \\ user while guaranteeing the \\ target rate of the weak user \\ \end{tabular} &
\begin{tabular}{c} Transmit beamforming, \\ IRS phase shift \\ \end{tabular} & (e) \\ \hline
[56] & Maximize the average sum rate &
\begin{tabular}{c} IRS passive beamforming, \\ UAV trajectory \\ \end{tabular} & (a) \\ \hline
[61] & Maximize the average sum rate &
\begin{tabular}{c} UAV trajectory, \\ IRS phase shift \\ \end{tabular} & (a) \\ \hline
[62] & Maximize the average average &
\begin{tabular}{c} Power splitting ratio, \\ transmit beamforming, \\ phase shift, \\ UAV trajectory \\ \end{tabular} & (a) \\ \hline
[63] & Maximize the minimum average &
\begin{tabular}{c} UAV trajectory, \\ IRS phase shift, \\ power control, \\ sub-band allocation \\ \end{tabular} & (a) \\ \hline
[64] & Maximize the sum rate &
\begin{tabular}{c} UAV trajectory, \\ IRS scheduling, \\ resource allocation \\ \end{tabular} & (a) \\ \hline
[65] & Maximize the minimum &
\begin{tabular}{c} Hover position, \\ beamforming vector of UAV, \\ IRS phase shift, \\ transmit power of UAV \\ \end{tabular} & (a) \\ \hline
[66] & Maximize the total throughput &
\begin{tabular}{c} Master UAV’s trajectory, \\ master UAV’s transmit power \\ \end{tabular} & (e) \\ \hline
[67] & Maximize channel capacity & IRS phase shift & (e) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of previous works relevant to improvement of spectral efficiency. The authors of [62] attempted to maximize the average achievable rate in a SWIPT system, wherein the intrinsic tradeoff between the spectral efficiency and energy efficiency was treated by considering the power-splitting ratio. Reference [63] aimed to maximize the minimum of the average achievable rates of all user equipment (UE) in an IRS-assisted UAV system operating in the THz spectrum. To achieve the goal, the authors proposed the optimization of the UAV trajectory, IRS phase shift, power control, and sub-band allocation of the THz spectrum. The proposed algorithm was shown to reduce the energy consumption of the UAVs, as well as improve the minimum achievable rate. Orthogonal frequency division multiple access (OFDMA) technology was applied to the IRS-assisted UAV system in [64]. The proposed approach achieved the maximum sum rate by jointly optimizing the trajectory of the UAVs and resource allocation in the IRS. The results confirmed that the size of the IRS affects the UAV trajectories and the achievable rates of users in the network. The authors of [65] proposed a method to minimize system throughput while satisfying the QoS of users. The system considered multi-antenna UAVs and ensured the energy requirements of energy-harvesting receivers. The IRS was used as a relay to help improve the communication performance. Reference [66] proposed a dual-UAV structure with a master UAV and a slave UAV to maximize the cumulative system throughput. Specifically, the slave UAV equipped with an IRS was adopted to strengthen the signals for the master UAV. The authors of [67] examined the channel capacity maximization and showed that the change in channel capacity due to phase error depends on the number of element antennas in the IRS.