Recently, unmanned aerial vehicles (UAVs) have been used as flying base stations (BSs) to take advantage of line‐of‐sight (LOS) connectivity and efficiently enable fifth‐generation (5G) and cellular network coverage and data rates. On the other hand, nonorthogonal multiple access (NOMA) is a promising technique to help achieve unprecedented requirements by simultaneously allowing multiple users to send data over the same resource block. In this paper, we study a UAV‐enabled uplink NOMA network, where the UAV collects data from ground users while flying at a certain altitude. Unlike all existing work on this topic, this study consists of two stages. In the first stage, we use the well‐known Particle Swarm Optimization (PSO) algorithm, which is a metaheuristic algorithm, to deploy the UAV in 3D space, so that the users’ sum pathlosses are minimized. In the second stage, we investigate the user pairing problem and propose a dynamic power allocation technique for determining the user’s power allocation coefficients, as well as a closed‐form equation for the ergodic sum‐rate. Results show our PSO‐based algorithm prevailing over the Genetic Algorithm (GA) and random deployment methods. The proposed dynamic power allocation strategy maximizes the network’s ergodic sum‐rate and outperforms the fixed power allocation strategy. Additionally, the results reveal that the best pairing scheme is the one that keeps uniform channel gain difference in the same pair.

Unmanned aerial vehicles (UAVs), also named as drones, have become a modern model to provide a quick wireless communication infrastructure. They have been used when conventional base stations’ capacity is suffering in some extreme cases such as congestion inside the cell or a special event. This paper proposes an efficient three‐dimension (3D) placement of a single UAV‐assisted wireless network in such cases. Our proposed model assists the ground base station (GBS) using the UAV to serve arbitrary distributed users considering the impact of the obstacle blockage over the well‐known air‐to‐ground (A2G) path model. This work is aimed at optimizing the percentage of available bandwidth that must be provided to the UAV in order to maximize the number of served users. In addition, it finds the 3D placement of the UAV base station (UAVBS) that maximizes the number of served users, each with maximum quality‐of‐service (QoS). The exhaustive search and particle swarm optimization (PSO) algorithms are used to find the problem’s solution.

Unmanned aerial vehicle (UAV) communication can be used in overcrowded areas and either during or postdisaster situations as an evolving technology to provide ubiquitous connections for wireless devices due to its flexibility, mobility, and good condition of the line of sight channels. In this paper, a single UAV is used as an aerial relay node to provide connectivity to wireless devices because of the considerable distance between wireless devices and the ground base station. Specifically, two path loss models have been utilized; a cellular‐to‐UAV path loss for a backhaul connection and an air‐to‐ground path loss model for a downlink connection scenario. Then, the tradeoff introduced by these models is discussed. The problem of efficient placement of an aerial relay node is formulated as an optimization problem, where the objective is to maximize the total throughput of wireless devices. To find an appropriate location for a relay aerial node that maximizes the overall throughput, we first use the particle swarm optimization algorithm to find the drone location; then, we use three different approaches, namely, (1) the equal power allocation approach, (2) water filling approach, and (3) modified water filling approach to maximize the total users’ throughput. The results show that the modified water filling outperforms the other two approaches in terms of the average sum rate of all users and the total number of served users. More specifically, in the best‐case scenario, it was observed that the average sum rate of the modified water filling is better than the equal power allocation and ensuring 100% coverage. In contrast, the water filling provides a very close average sum rate to the modified water filling, but it only provides a 28% user coverage.

Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider downlink scenarios from an aerial base station to ground users. In this paper, we consider an uplink scenario under disaster situations (such as earthquakes or floods), when cellular networks are down. We formulate the problem of optimal UAV placement, where the objective is to determine the placement of a single UAV such that the sum of time durations of uplink transmissions is maximized. We prove that the constraint sets of problem can be represented by the intersection of half spheres and the region formed by this intersection is a convex set in terms of two variables. This proof enables us to transform our problem to an optimization problem with two variables. We also prove that the objective function of the transformed problem is a concave function under a restriction on the minimum altitude of the UAV and propose a gradient projection-based algorithm to find the optimal location of the UAV. We validate the analysis by simulations and demonstrate the effectiveness of the proposed algorithm under different cases.

Cellular networks at millimeter wave frequencies experience tremendous propagation impairments and channel fluctuations. One major challenge here is the aggregated path loss levels attributed to obstacles of various shapes and density in the propagation links, i.e., link blockage. Therefore, once the base and mobile stations establish the optimum beamforming and combining vectors during the initial beam access procedure in the control-plane, efficient link maintenance techniques are required to maintain communication sessions with sufficient signal levels at various blockage densities. Hence this paper presents a novel link recovery scheme based upon beam aggregation during link transitions from line-of-sight to non-line-of-sight (NLoS) environments. The proposed scheme utilizes circular antenna arrays and hybrid beamforming designs to achieve near-instantaneous recovery times without the need for repeated beam scanning. Simulation results show that the proposed recovery scheme exhibits significant improvements compared to alternative traditional methods in terms of signal-to-noise ratios and recovery times.

Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider an Air-to-Ground path loss model, which assumes that the users are outdoor and they are located on a 2D plane. In this paper, we propose using a single UAV to provide wireless coverage for indoor users inside a high-rise building under disaster situations (such as earthquakes or floods), when cellular networks are down. First, we present a realistic Outdoor-Indoor path loss model and describe the tradeoff introduced by this model. Then, we study the problem of efficient UAV placement, where the objective is to minimize the total transmit power required to cover the entire high-rise building. The formulated problem is non-convex and is generally difficult to solve. To that end, we consider two cases of practical interest and provide the efficient solutions to the formulated problem under these cases. In the first case, we aim to find the minimum transmit power such that an indoor user with the maximum path loss can be covered. In the second case, we assume that the locations of indoor users are symmetric across the dimensions of each floor.