Search

The line-of-sight (LoS) condition is important to the quality of wireless communications, especially for millimeter-wave (mmWave) communications which are more sensitive to blockages than typical radio frequency (RF) communications. Considering that one blockage would obstruct several channels simultaneously, recently, researchers have studied the correlation of LoS probabilities among multiple channels in the horizontal plane and shown its importance in system performance analysis. The main missing aspect of existing literature in this direction is that the heights of transceivers and blockages have not been considered in the analysis of the LoS correlation. However, the emerging hybrid cellular networks with unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) deployed at various altitudes necessitate the LoS analysis accounting for the vertical dimension. In this paper, using stochastic geometry, we formulate a novel joint-LoS-probability framework of two channels among three aerial/terrestrial devices to analyze the LoS correlation both in the horizontal and vertical dimensions. We derive the expression of the conditional and joint LoS probabilities. The proposed framework combines (i) accuracy (verified in simulation), (ii) generality (from adjustable parameters of the channels and environments), and (iii) fitting ability (from a cylindrical blockage model to a non-cylindrical blockage model). The numerical results show that the correlation is quite strong when the angle between the two communication channels is small, while it becomes weaker as this angle increases. Moreover, we introduce a potential application of the joint LoS probability in the optimal deployment of an aerial device. Compared to optimization based on the independence assumption of the LoS probabilities, the improvement in the coverage probability intuitively clarifies the advantage of the proposed joint-LoS-probability framework on the aerial-terrestrial network design.

This article proposes, and evaluates the benefit of, one particular hybrid satellite-high-altitude-platform-station (HAPS)-ground network, where one HAPS connected to one geo-satellite assists the ground base stations (BSs) at serving ground-level users. The paper assumes that the geo-satellite is connected to the HAPS using free-space-optical backhaul links. The HAPS, equipped with multiple antennas, aims at transmitting the geo-satellite data to the users via radio-frequency (RF) links using spatial-multiplexing. Each ground BS, on the other hand, is equipped with multiple antennas, but directly serves the users through the RF links. The paper then focuses on maximizing the network-wide throughput, subject to HAPS payload connectivity constraint, HAPS and BSs power constraints, and backhaul constraints, so as to jointly determine the user-association strategy of each user (i.e., user to geo-satellite via HAPS, or user to BS), and their associated beamforming vectors. We tackle such a mixed discrete-continuous optimization problem using an iterative approach, where the user-association is determined using a combination of integer linear programming and generalized assignment problems, and where the beamforming strategy is found using a weighted-minimum-mean-squared-error approach. The simulations illustrate the appreciable gain of our proposed algorithm, and highlight the prospects of augmenting the ground networks with beamforming-empowered HAPS for connecting the unconnected, and super-connecting the connected.

Aiming to expand wireless coverage and connect the unconnected, space-air-ground integrated networks (SAGIN) have recently been proposed as a promising paradigm to satisfy the high-rate and high-reliability requirements. SAGIN is comprised by satellite, aerial, and terrestrial communication devices. In this article, from the perspective of cooperative communications, we regard the SAGIN as a two-hop relay network with the space-air and air-ground cooperative links. Especially, the location distribution of unmanned aerial vehicle (UAV), as known as the communication relay platforms in the SAGIN system, is modeled as a homogeneous Poisson Point Process (PPP) in a three-dimensional (3D) spherical field. We evaluate the outage performance of SAGIN in the 3D Poisson field and approximate its outage probability in closed form. In addition, the parametric study for the approximation technique used to derive the closed-form expression is also provided. Numerical results are presented and discussed to verify our outage performance analysis.

With the advancements achieved in drones' flexibility, low cost, and high efficiency, they obtain huge application opportunities in various industries, such as aerial delivery and future communication networks. However, the increasing transportation needs and expansion of network capacity demands for UAVs will cause aerial traffic conflicts in the future. To address this issue, in this article, we explore the idea of multi-purpose UAVs, which act as aerial wireless communication data relays and means of aerial transportation simultaneously to deliver data and packages at the same time. While UAVs deliver the packages from warehouses to residential areas, we design their trajectories which enable them to collect data from multiple Internet of Things (IoT) clusters and forward the collected data to terrestrial base stations (TBSs). To select the serving nearby IoT clusters, UAVs rank them based on their priorities and distances. From the perspectives of data and package delivery, respectively, we propose two algorithms that design the optimal UAVs trajectory to maximize the transmitted data or minimize the round trip time. Specifically, we use tools from stochastic geometry to model the locations of IoT clusters and TBSs. Given the nature of random locations, the proposed algorithm applies to general cases. Our numerical results show that multi-purpose UAVs are practical and have great potential to enhance the energy/time-efficiency of future networks.

Received signal strength (RSS)-based localization techniques are widely used to estimate the location of wireless sensor nodes as they utilize minimum bandwidth and do not require additional hardware.However, these techniques typically assume that the nodes' transmit power is known, despite the fact that changes in transmit power, influenced by factors such as antenna orientation and battery level, can significantly impact localization performance. To address this issue, we propose an RSS-based cooperative localization technique that jointly estimates the location and transmit power of the nodes and will refer to it as FCUP (Fast Cooperative localization technique with Unknown transmit Power). The maximum likelihood (ML) estimator for joint estimation of location and transmit power is non-convex, discontinuous, and computationally challenging to solve. So, we reformulate the optimization problem into a mixed semidefinite second-order cone program (SDP-SOCP) using the Taylor expansion, epigraph method, and semidefinite relaxation. FCUP takes advantage of the high accuracy of SDP and the low complexity of SOCP. FCUP is compared to the existing techniques to demonstrate its superior performance based on localization accuracy, computational complexity, and execution time.

Recent advances demonstrate satellite communication (SatCom) as a potent enabler for future Terabit/s global connectivity. Existing SatCom systems, however, rely mostly on radio frequency (RF) transmission, whose limited available bandwidth is the main bottleneck for further data rate increases. Free-space optical (FSO) communication links, with huge license-free bandwidth, have emerged as an attractive alternative. Despite their ability to deliver high-throughput transmissions, FSO communications are weather-dependent and susceptible to atmospheric turbulence. Hybrid FSO/RF and space-air-ground (SAG) FSO transmissions are possible solutions to increase the reliability of FSO-based transmission systems. A strategically deployed unmanned-aerial vehicle, acting as a relay, can successfully mitigate the adverse effect of atmospheric turbulence, while the hybrid FSO/RF transmission can address weather-dependent effects. These solutions can also be integrated to create a system with significantly improved performance and reliability. To evaluate the performance of the resulting integrated transmission system, we analyze the outage probability and average symbol error probability in this work. Asymptotic expressions are also derived to obtain further insight into the system behavior and calculate the overall diversity gain. Furthermore, we consider the optimal design of switching thresholds. The numerical results show that the integrated transmission system achieves about 10 dB performance gain over existing solutions for both downlink and uplink scenarios.