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This paper proposes an exhaustive analysis of a particle swarm optimization (PSO)-based configuration applied in non-orthogonal multiple access (NOMA) systems in order to perform user aggregation along different sub-channels. The idea behind this is to highlight the main characteristics of this PSO-based configuration for understanding how this policy enables the transmitter to require the minimum downlink transmitting power while guaranteeing the quality-of-service (QoS) constraint of each user. The analysis is carried out for two representative power-constrained scenarios, i.e., disaster relief network communications and unmanned aerial vehicle (UAV) communications, in which performing low-power transmissions represent an important aspect. Our results find applicability in the definition of explicit channel-state-aware strategies for user multiplexing in NOMA systems, which, at the date, represents a research field that remains to be investigated more in depth. Insightful discussions are provided from our analysis. For instance, depending on the number of available sub-channels and the channel gains experienced by each users along with the whole available bandwidth, it is shown how users must be multiplexed by the transmitter in order to reach the minimum transmitting power.

In this paper, we propose an aerial reconfigurable intelligent surface (RIS) system to support the stringent constraints of ultra-reliable low latency communication (URLLC). Specifically, unmanned aerial vehicles (UAVs) employed onboard RIS panels can act as repeaters to reflect the signal from macro base station (MBS) to all users in the networks. To overcome the dense networks' interference, we propose to use zero-forcing beamforming and time division multiplexing access (TDMA) scheme where each UAV can serve a number of users in its own cluster. We formulate a optimisation framework in terms of UAVs' deployment, power allocation at MBS, phase-shift of RIS, and blocklength of URLLC. Due to highly nonconvex and complex optimisation problem, we first consider to use a deep neural network (DNN) to solve the optimal UAVs' deployment. Then, the optimal resource allocation is proposed to provide the maximal reliability of the considered system with respect to the users' fairness. From the representative numerical results, our proposed scheme is shown to superior to other benchmarks which exhibits the positive impact of aerial RIS in supporting stringent demands of URLLC.INDEX TERMS Ultra-reliable low-latency communications (URLLC), Reconfigurable Intelligent Surface (RIS), Unmanned aerial vehicle (UAV).

Wireless power transfer (WPT) techniques are important in a variety of applications in both civilian and military fields. Unmanned aerial vehicles (UAVs) are being used for many practical purposes, such as monitoring or delivering payloads. There is a trade-off between the weight of the UAVs or their batteries and their flying time. Their working time is expected to be as long as possible. In order to support the UAVs to work effectively, WPT techniques are applied with UAVs to charge secondary energy supply sources in order to increase their working time. This paper reviews common techniques of WPT deployed with UAVs to support them while working for different purposes. Numerous approaches have been considered to illustrate techniques to exploit WPT techniques. The charging distances, energy harvesting techniques, electronic device improvements, transmitting issues, etc., are considered to provide an overview of common problems in utilizing and charging UAVs. Moreover, specific problems are addressed to support suitable solutions with either techniques or applications for UAVs.