This paper considers and analyzes the performance of a non-orthogonal multiple access (NOMA) system using finite-size data packets with the assistance of active reconfigurable intelligent surfaces (ARISs) mounted on an unmanned aerial vehicle (UAV). This work aims to enhance communication efficiency in scenarios that require low latency and high reliability. The exact and asymptotic closed-form expressions for the block error rate (BLER) and average achievable rate (AAR) of the considered UAV-ARIS-NOMA system with short packet communication under imperfect successive interference cancellation (SIC) are derived. The results analysis indicates that the number of reflection elements strongly influences the diversity order. The considered system meets ultra-reliable and low-latency communications (URLLC) demands with 99.999% reliability, and the ARIS model's BLER reduces by 290% compared to the passive RIS (PRIS). Moreover, the gap between the AAR of ARIS and PRIS is up to 40% when configuring eight reflection elements. The system's AAR reaches saturation by adjusting the ARIS amplification factor to three power units. When channel uses exceed 300, the system's transmission rate meets the Shannon rate. Moreover, simulation results are introduced to verify the theoretical analysis and offer insights into optimizing power allocation and UAV altitude to minimize BLER.

This paper analyzes and solves the optimization problem of the performance of a multi-antenna unmanned aerial vehicle (UAV)-aided NOMA multi-user pairing system. Based on the approximation of the Gaussian-Chebyshev quadrature and incomplete Gamma function, we successfully derive the exact and asymptotic closed-form expressions for the block error rate, throughput, and goodput of the system. Moreover, we also provide other metrics such as the latency, reliability, and age of information (AoI). The results indicate that the considered system meets the requirements of ultra-reliable and low-latency communications (URLLC). Particularly, its reliability is higher than 99.99% and latency is less than 1 ms. The optimization of the UAV's altitude, block length, and the number of transmission bits to maximize the throughput and minimize the latency and AoI of the considered system is also studied by using iterative algorithms. Furthermore, we propose an algorithm to optimize the transmission power of UAVs to maximize the system's energy efficiency. The greedy algorithm is used to schedule paired users and achieves better performance compared to the random schedule. Moreover, applying multiple antennas and maximum ratio transmission can significantly improve the latency and AoI performance of the considered system. The accuracy of analytical frameworks is verified by simulation results.

In this work, we consider a base station (BS) mounted on an unmanned aerial vehicle (UAV) called as an aerial BS (ABS). The ABS is equipped with multiple antennas to assist two pairs of users in nonorthogonal multiple access (NOMA) scheme, and it serves as a relay station to forward the data from the uplink to the downlink of ground IoT users in half-duplex mode. Moreover, the communication power of ABS is harvested from ambient radio-frequency (RF) sources, such as television (TV) and radio signals via the time switching mechanism. In order to improve the efficiency of harvested energy, multiple antennas at the TV/radio tower and the maximal-ratio transmission (MRT) scheme are applied. The proposed ABS RF energy harvesting system overcomes the problem of connectivity of ground IoT users and the energy limitation of devices. The system performance is evaluated in terms of the outage probability of each pair of IoT users in various urban communication environments. Monte Carlo simulation results are provided to validate the accuracy of the developed analytical results and also demonstrate the performance of the proposed system. The results show that the proposed system achieves better performance than that of benchmark systems and the performance can be improved significantly by adjusting the UAV’s altitude.