Unmanned aerial vehicles (UAVs) have been widely employed in wireless communications, and the performance can be enhanced with the assistance of intelligent reflecting surface (IRS). However, the finite energy of UAVs greatly limits the endurance and becomes a bottleneck for IRS-UAV communications. In this paper, an integrated IRS-UAV communication scheme is proposed where the IRS is mounted on the UAV to connect the base station and the ground user. We present two schemes to maximize the spectrum efficiency (SE) and the energy efficiency (EE) of the system by jointly optimizing the active beamforming, passive beamforming and UAV trajectory. First, to tackle the SE maximization problem, we divide it into three subproblems to optimize the variables iteratively. For the active and passive beamforming, the closed-form solutions can be directly derived. The suboptimal trajectory design can be obtained by utilizing the successive convex approximation. Furthermore, considering the limited on-broad energy of UAV, a scheme to maximize the EE is proposed. The optimal active beamforming and the passive beamforming can be similarly obtained. For the non-convex fractional programming of trajectory optimization, it can be solved via the Dinkelbach’s method. Numerical results demonstrate that the proposed algorithms are effective for the IRS-UAV networks to maximize the SE and EE, respectively.

In this correspondence, covert air-to-ground communication is investigated to hide the wireless transmission from unmanned aerial vehicle (UAV). The warden's total detection error probability with limited observations is first analyzed. Considering the location uncertainty of the warden, a robust resource allocation and UAV trajectory optimization problem with worst-case covertness constraint is then formulated to maximize the average covert rate. To solve this optimization problem, we propose a block coordinate descent method based iterative algorithm to optimize the time slot allocation, power allocation and trajectory alternately. Numerical results demonstrate the effectiveness of the proposed algorithm in covert communication for UAVs.

Unmanned aerial vehicle (UAV) is suitable to improve connectivity of wireless communication networks in harsh environment due to its flexible deployment and high mobility. In this paper, we consider the case that a UAV is employed as a mobile relay to ferry data between two disconnected ground nodes. The amplify-and-forward mobile relay technique is studied. By exploiting the channel state variation induced by the movement of UAV, we consider maximizing the end-to-end throughput of this mobile relay system by optimizing the source/relay power allocation, as well as the UAV's trajectory. However, the formulated problem is non-convex and intractable to solve. To address this non-convex problem, we propose two iterative algorithms to optimize the source/relay power allocation with the fixed UAV's trajectory and the UAV's trajectory with fixed power allocation, by successive convex optimization, respectively. Then, an iterative algorithm is proposed to optimize the source/relay power allocation and UAV's trajectory in an alternate manner. By exploiting the predictable channel variation via the proposed power and trajectory optimization scheme, numerical results show that significant throughput gains can be achieved.

High-precision positioning scheme, an important part of indoor navigation, can be implemented using an ultra-wideband (UWB) based ranging system. Recently, solutions for precise positioning in dense multipath and non-line-of-sight (NLOS) conditions have attracted a lot of attentions. On the other hand, it is expected that waveform division multiple access (WDMA) technology for multiuser UWB positioning applications will be indispensable in the near future. In this regard, a WDMA-UWB-based positioning scheme is investigated in this paper, to enhance the positioning accuracy in multiuser applications. In accordance with practical requirements of indoor positioning, we propose a new indoor positioning scheme, termed as WDMA-UWB-based indoor positioning (WUB-IP). This scheme adopts WDMA for multiple access, and utilizes an entropy-based approach for the time of arrival estimation. Moreover, a transfer learning approach is used to mitigate the ranging error in NLOS conditions, in order to improve the positioning accuracy in NLOS conditions. System-level simulations demonstrate that the proposed scheme enhances the performance of indoor positioning for multiuser applications.