Abstract
The recent applications of Unmanned Aerial Vehicles (UAVs) and Remotely Piloted Air Systems (RPAS) often require reliable and fast two-way communications between UAVs, base stations and consumers using terrestrial cellular networks. Two crucial questions are whether existing ground networks can effectively interact with UAVs in three-dimensional space during intensive traffic and under what data transmission modes it is possible to provide the necessary Quality of Service (QoS). To answer this question, the UAV/RPAS communication channel model “BS-ATM-HUB-RPAS” with a ground network was designed and investigated. The dependencies of dropped packets, message Travel Time (TT) and HUB Average Utilization on the Transaction Size (TS), the link bandwidth, the Bit Error Rate (BER) and the Packet Fail Chance for different distribution laws of Time Between Transactions (TBT) were analyzed. A significant benefit has been observed in using the LogNormal TBT distribution law rather than the Const and Exponential TBT distributions for the dependencies of dropped packets versus TS, HUB Average Utilization versus TS, and HUB Average Utilization versus link bandwidth. However, for the dependency of message Travel Time on the Transaction Size, the type of TBT distribution did not play a significant role; for all distributions, with increasing transaction size, the time of their transmission via the channel was increased. The importance and usefulness of such a numerical analysis lies in the ability to set traffic parameters and observe the resulting throughput, packet loss, and number of bit errors and QoS in a channel under certain transmission modes.
Highlights
AND ANALYSIS OF PUBLICATIONSThe increased functionality and reduced operating costs of Unmanned Aerial Vehicles (UAVs) and Remotely Piloted Air Systems (RPAS) has led to an increase in their use as airborne wireless platforms for connecting ground users, the Internet of Things (IoT) and the Internet of Drones (IoD)
This paper extends previous investigations, where the use of a UAV swarm was considered as flying access points forming a mesh network among themselves, providing connectivity to ground nodes
The results show that the path loss exponent decreases as the UAV moves upward
Summary
The increased functionality and reduced operating costs of Unmanned Aerial Vehicles (UAVs) and Remotely Piloted Air Systems (RPAS) has led to an increase in their use as airborne wireless platforms for connecting ground users, the Internet of Things (IoT) and the Internet of Drones (IoD). The proposed methods for this integration overcome the limitations of ground-based infrastructure, covered areas and the increasing number of IoT devices It was shown in [12] that the use of RPAS in combination with a conventional network can improve the cellular system. The capabilities of traffic parameter predictions using the NetCracker software application were tested in our publication [14] in 2014, where dependencies of message traveling time (1.4 – 1.9 s) on the number of satellites and aircraft were obtained These calculated data were experimentally confirmed in 2017, when Aireon provided air traffic surveillance data to its partners NavCanada, NATS, ENAV, IAA, and the FAA [15]. By tracking over 10,000 aircraft, the system delivered data to air traffic control centers with a latency of under 1.5 s [16] These data practically coincided with our previously calculated values and confirmed the realism of the results obtained for communication channel models using NetCracker software. Simulations of RPAS data transmission via satellites using MATLAB and NetCracker software were described in our papers [17–20], where satellite channel parameters based on IEEE 802.11a, 802.11 b, 802.16 and Long-Term Evolution (LTE) standards and RPAS satellite traffic characteristics were estimated
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
