Measurement Based Statistical Channel Characterization of Air-to-Ground Path Loss Model at 446 MHz for Narrow-Band Signals in Low Altitude UAVs

Powered by the advances in microelectronics technologies, unmanned aerial vehicles (UAVs) provide a vast variety of services ranging from surveillance to delivery in both military and civilian domains. It is clear that a successful operation in those services relies heavily on wireless communication technologies. Even though wireless communication techniques could be considered to reach a certain level of maturity, wireless communication links including UAVs should be regarded in a different way due to the peculiar characteristics of UAVs such as agility in 3D spatial domain and versatility in modes of operation. Such mobility characteristics in a vast variety of environmental diversity render links including UAVs different from those in traditional, terrestrial mobility scenarios. Furthermore, UAVs are critical instruments for network operators in order to provide basic voice and short messaging services for narrow band communication in and around disaster areas. It is obvious that such widespread use of UAVs under different scenarios and environments requires a better understanding the behavior of the communication links that include UAVs. Therefore, in this study, details of a measurement campaign designed to collect data for large-scale propagation characterization of air-to-ground links operated by UAVs at 446MHz under narrowband assumption are given. Data collection, post-processing, and measurement results are provided.Comment: This work is accepted to 2020 IEEE 91st Vehicular Technology Conference: VTC2020-Spring on January 11, 202

The Performance Analysis of Spectrum Sharing between UAV enabled Wireless Mesh Networks and Ground Networks

Unmanned aerial vehicle (UAV) has the advantages of large coverage and flexibility, which could be applied in disaster management to provide wireless services to the rescuers and victims. When UAVs forms an aerial mesh network, line-of-sight (LoS) air-to-air (A2A) communications have long transmission distance, which extends the coverage of multiple UAVs. However, the capacity of UAV is constrained due to the multiple hop transmissions in aerial mesh networks. In this paper, spectrum sharing between UAV enabled wireless mesh networks and ground networks is studied to improve the capacity of UAV networks. Considering two-dimensional (2D) and three-dimensional (3D) homogeneous Poisson point process (PPP) modeling for the distribution of UAVs within a vertical range {\Delta}h, stochastic geometry is applied to analyze the impact of the height of UAVs, the transmit power of UAVs, the density of UAVs and the vertical range, etc., on the coverage probability of ground network user and UAV network user. Besides, performance improvement of spectrum sharing with directional antenna is verified. With the object function of maximizing the transmission capacity, the optimal altitude of UAVs is obtained. This paper provides a theoretical guideline for the spectrum sharing of UAV enabled wireless mesh networks, which may contribute significant value to the study of spectrum sharing mechanisms for UAV enabled wireless mesh networks.Comment: 12 pages, 13 figures, IEEE Sensors Journa

Positioning of multiple unmanned aerial vehicle base stations in future wireless network

Abstract. Unmanned aerial vehicle (UAV) base stations (BSs) can be a reliable and efficient alternative to full fill the coverage and capacity requirements when the backbone network fails to provide the requirements during temporary events and after disasters. In this thesis, we consider three-dimensional deployment of multiple UAV-BSs in a millimeter-Wave network. Initially, we defined a set of locations for a UAV-BS to be deployed inside a cell, then possible combinations of predefined locations for multiple UAV-BSs are determined and assumed that users have fixed locations. We developed a novel algorithm to find the feasible positions from the predefined locations of multiple UAVs subject to a signal-to-interference-plus-noise ratio (SINR) constraint of every associated user to guarantees the quality-of-service (QoS), UAV-BS’s limited hovering altitude constraint and restricted operating zone because of regulation policies. Further, we take into consideration the millimeter-wave transmission and multi-antenna techniques to generate directional beams to serve the users in a cell. We cast the positioning problem as an ℓ₀ minimization problem. This is a combinatorial, NP-hard, and finding the optimum solution is not tractable by exhaustive search. Therefore, we focused on the sub-optimal algorithm to find a feasible solution. We approximate the ℓ₀ minimization problem as non-combinatorial ℓ₁-norm problem. The simulation results reveal that, with millimeter-wave transmission the positioning of the UAV-BS while satisfying the constrains is feasible. Further, the analysis shows that the proposed algorithm achieves a near-optimal location to deploy multiple UVABS simultaneously

Environment-Aware Drone-Base-Station Placements in Modern Metropolitans

Unmanned aerial vehicles, i.e, drones, have recently caught attention for providing on-demand capacity to wireless networks as drone-base-stations (drone-BSs). Many studies assume simplified channel models based on average characteristics of the environment to estimate the placement of drone-BSs. However, especially in urban areas, positioning of drone-BSs with respect to intersections and roof-top heights of buildings can severely change the path loss characteristics. To address this issue, we adopt an ITU channel model utilizing more information about the environment, such as the shapes of the buildings. We optimize parameters of the selected ITU model, so that it can be used for altitudes both strictly lower and higher than building roof-tops. Using ray-tracing simulations as a benchmark, we compare the proposed model with a widely used simpler model. Results show that the proposed model can reduce the root-mean-squared error from 35 dB to 10 dB, which may have critical implications for drone-BS operations, such as planning for the required number of drone-BSs to cover outdoor urban users, as demonstrated with simulations

End-to-end delay analysis for routing protocols in VANETs

Vehicular ad-hoc network (VANET) technology enables communication between vehicles, or vehicles and road-side units (RSUs) through wireless communication devices installed on the vehicles. One of the most important goals of VANETs is providing safety applications for passengers. In addition, VANETs provide comfort applications to users. Guaranteeing a reliable and stable routing protocol over VANETs is a very important step. The proposed research attempts to improve routing protocols that decrease the end-to-end delay to suit VANET communication characteristics. In addition, it proposes analysis of the end-to-end delay probability distribution. More specifically, we derive a closed-form expression for the probability distribution of the re-healing delay in a VANET conditioned on the distance between two VANET clusters. Furthermore, we propose a closed-form expression for the probability distribution of the unconditional re-healing delay. Moreover, we develop a mathematical model to calculate the probability distribution of the end-to-end delay. On the other hand, using Unmanned Aerial Vehicles (UAVs) or drones in wireless communications and Vehicular Ad-hoc Networks (VANETs) has started to attract attention. We propose a routing protocol that uses infrastructure drones for boosting VANET communications to achieve a minimum vehicle-to-drone packet delivery delay. In addition, we propose a closed-form expression for the probability distribution of the vehicle-to-drone packet delivery delay on a two-way highway. Moreover, based on that closed-form expression, we can calculate the minimum drone density (maximum separation distance between two adjacent drones) that stochastically limits the worst case of the vehicle-to-drone packet delivery delay. Furthermore, we propose a drones-active service (DAS) that is added to the location service in a VANET. This service dynamically and periodically obtains the required number of active drones based on the current highway connectivity state by obtaining the maximum distance between each two adjacent drones while satisfying a probabilistic constraint for vehicle-todrone packet delivery delay. Our analysis focuses on two-way highway VANET networks with low vehicular density. The simulation results show the accuracy of our analysis and reflect the relation between the drone density, vehicular density and speed, other VANET parameters, and the vehicle-to-drone packet delivery delay. In addition, we propose a new routing protocol called multi-copy intersection-based routing (MCIR) for vehicular ad-hoc networks (VANETs) in urban areas. MCIR is an intersectionbased routing protocol that forwards multiple copies of the packets in different road segments. Moreover, it is a beacon-less routing protocol with a carry-and-forward strategy. We show via simulation that the MCIR protocol is superior to other existing routing protocols, especially in low vehicular density scenarios. The results show that MCIR achieves a shorter end-to-end delay and a higher packet delivery ratio in urban VANET communications

Unmanned aerial vehicles (UAVs) for wireless communication and networks : potentials and design challenges

Unmanned aerial vehicles (UAVs) are mostly considered by the military for surveillance and reconnaissance operations, and by hobbyists for aerial photography. However, in recent years, the UAV operations have been extended for civilian and commercial purposes due to their agile and cost-effective deployment. UAVs appear to be more prolific platforms to enable wireless communication due to their better line-of-sight (LOS) channel conditions as compared with the fixed base stations (BSs) in terrestrial communication which suffer from severe path loss, shadowing, and multipath fading in more challenging propagation environments. In UAV-enabled wireless communications, the UAV can either act as a complementary aerial BS to provide on-demand communication or as an aerial user equipment (UE) which is operated by the existing cellular network. Several challenges exist in the design of UAV communications which include but not limited to channel modeling, optimal deployment, interference generation, performance analysis, limited on-board battery lifetime, trajectory optimization, and unavailability of regulations and standards which are specific for UAV communication and networking. This thesis particularly investigates some important design challenges for safe and reliable functionalities of UAV for wireless communication and networking. UAV communication has its own distinctive channel characteristics compared to the widely used cellular or satellite systems. However, several challenges exist in UAV channel modeling. For example, the propagation characteristics of UAV channels are under explored for spatial and temporal variations in non-stationary channels. Therefore, first and foremost, this thesis provides an extensive review of the measurement methods proposed for UAV channel modeling and discusses channel modeling efforts for air-to-ground and air-to-air channels. Furthermore, knowledge-gaps are identified to realize accurate UAV channel models. The efficient deployment strategy is imperative to compensate the adverse impact of interference on the coverage area performance of multiple UAVs. As a result, this thesis proposes an optimal deployment strategy for multiple UAVs in presence of downlink co-channel interference in the worst-case scenario. In particular, this work presents coordinated multi-UAV strategy in two schemes. In the first scheme, symmetric placement of UAVs is assumed at a common optimal altitude and transmit power. In the second scheme, asymmetric deployment of UAVs with different altitudes and transmit powers is assumed. The impact of various system parameters, such as signal-to interference-plus-noise ratio (SINR) threshold, separation distance between UAVs, and the number of UAVs and their formations are carefully studied to achieve the maximum coverage area inside and to reduce the unnecessary coverage expansion outside the target area. Fundamental analysis is required to obtain the optimal trade-off between the design parameters and performance metrics of any communication systems. This thesis particularly considers two emerging scenarios for evaluating performance of UAV communication systems. In the first scenario, the uplink UAV communication system is considered where the ground user follows the random waypoint (RWP) model for user mobility, the small-scale channel fading follows the Nakagami-m model, and the uplink interference is modeled by Gamma approximation. Specifically, the closed-form expressions for the probability density function (PDF), the cumulative distribution function (CDF), the outage probability, and the average bit error rate (BER) of the considered UAV system are derived as performance metrics. In the second scenario, the downlink hybrid caching system is considered where UAVs and ground small-cell BSs (SBSs) are distributed according to two independent homogeneous Poisson point processes (PPPs), and downlink interference is modeled by the Laplace transforms. Specifically, the analytical expressions of the successful content delivery probability and energy efficiency of the considered network are derived as performance metrics. In both scenarios, results are presented to demonstrate the interplay between the communication performance and the design parameters