Satellite Traffic Simulation for RPAS Swarms

Grekhov, Andriy; Kondratiuk, Vasyl; Ilnytska, Svitlana; Vyshnyakova, Yevheniya; Kondratiuk, Maryna; Trykoz, Valeriy

doi:10.1109/apuavd47061.2019.8943881

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…The operation of SAGIN is impossible without reliable communication channels between all components. Our previous works [12,13,[22][23][24][25][26][27][28][29][30][31][32][33] were devoted to the study of SAGIN communication channels using MATLAB Simulink and NetCracker software.…”

Section: Problem Statement and Aimmentioning

confidence: 99%

Traffic Simulation in SAGIN Air Segment Containing Ad Hoc Network of Flying Drones

Kharchenko¹,

Grekhov²,

Kondratiuk³

2022

Preprint

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The purpose of this article is to simulate data transmission and calculate traffic parameters in SAGIN air segment for which Ad Hoc network of flying drones is considered as a model. Traffic modeling is based on the manet-routing-compare example from the ns3 simulator library, which has been supplemented with the code for calculation packet losses, throughput/goodput, and message transmission delays. The program allowed considering drones movement at both low and high speeds from 3.6 km/h to 72 km/h. The dependences of traffic losses on data transmission power, transaction sizes and data transmission rate are obtained and analyzed. The distribution of the average effective arrival rate λ and the throughput/goodput for drones has been studied. Comparing traffic characteristics in models with different numbers of drones allows judging how the required quality of service can be achieved by choosing the right transmission parameters.

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Section: Problem Statement and Aimmentioning

confidence: 99%

Traffic Simulation in SAGIN Air Segment Containing Ad Hoc Network of Flying Drones

Kharchenko¹,

Grekhov²,

Kondratiuk³

2022

Preprint

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“…Therefore, the number of publications devoted to these issues is constantly increasing. In recent years, many books, reviews, tutorials [3][4][5][6][7][8][9][10][11][12][13][14] and articles [15][16][17][18][19][20][21][22][23][24][25][26][27] have been published. This article is based on our preprint (https://doi.org/10.21203/rs.3.rs-885685/v1) and uses a centralized two-way Radio Line of Sight (RLOS) connection of a ground station with all drones in a swarm.…”

Section: Introductionmentioning

confidence: 99%

Studying Data Loss, Nonlinearity, and Modulation Effects in Drone Swarms with Artificial Intelligence

Kharchenko

Grekhov

Kondratiuk

2023

Preprint

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Artificial Intelligence (AI) of drone swarms depends on reliable communications. The parallelism and distributed characteristics of swarm intelligence provide self-adapting and reliable capabilities. This article is devoted to the calculation of packet losses and the impact of traffic parameters on the data exchange in swarms. Original swarm models were created with the help of MATLAB and NetCracker packages. Dependences of data packet losses on the transaction size are calculated for different drone number in a swarm using NetCracker software. Data traffic with different parameters and statistical distribution laws was considered. The effect of different distances to drones on the base station workload has been simulated. Data transmission in a swarm was studied using MATLAB software depending on the signal-to-noise ratio, nonlinearity levels of base station amplifier, signal modulation types, base station antenna diameters, and signal phase offsets. The data obtained allows foresee the operation of drone communication channels in swarms.

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“…This study was undertaken to understand the ways of fulfilling the requirements for SAGIN's delay, reliability, bandwidth, and QoS and explore the approaches for solving these problems. The issues of creating and using SAGIN are considered in articles (Bithas et al, 2019; Grekhov et al, 2020a, 2020b; Grekhov, Kondratiuk, et al, 2019; Liu et al, 2018; Marchese et al, 2019; Wang et al, 2016; Xiong et al, 2016; Yan et al, 2019; Yang et al, 2019; Yao et al, 2018; Zhang et al, 2017; Zhu et al, 2017), and reviews (Grekhov, 2019; Yan et al, 2019) are devoted to modeling RPAS/UAV communication channels.…”

Section: Introduction Analysis Of Publications and Aim Of Workmentioning

confidence: 99%

“…IoT and UAV integration in 5G Hybrid Terrestrial‐Satellite Networks was considered in paper (Marchese et al, 2019). Modeling of aircraft and RPAS data transmission via satellites using MATLAB and NetCracker software were investigated in our works (Grekhov, 2019; Grekhov et al, 2020a, 2020b; Grekhov, Kondratiuk, et al, 2019).…”

Section: Introduction Analysis Of Publications and Aim Of Workmentioning

confidence: 99%

Modeling of UAV/RPAS data traffic in space, air, and ground networks

Ilnytska

Grekhov

Kondratiuk

2021

Journal of Field Robotics

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Remotely piloted air systems (RPASs) are increasingly used for data transmission in the space‐air‐ground integrated networks (SAGINs). That is why it is important to know the possibilities and ways of integrating existing space, air and terrestrial networks for effective interaction with RPASs. This paper studies the issues of ensuring the required quality of service during heavy traffic in SAGIN and the choice of the necessary data transmission modes for this. Models of communication channels were created, including line‐of‐sight transmission (Model 1), public terrestrial network (PTN) (Model 2), low‐orbit satellite transmission (Model 3) and PTN plus satellite transmission (Model 4). The relationships between models' performance and traffic parameters, channel bandwidths, bit errors, lost packets and models' topology were investigated using NetCracker Professional 4.1 software. The dependencies of the average utilization on the transaction size and the time between transactions with different statistical distribution laws were analyzed. The effect of different bandwidths was investigated. The influence of the bit error rate and the probability of packet fail chance on the channel performance was studied. The traffic characteristics in all models were compared.

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Satellite Traffic Simulation for RPAS Swarms

Cited by 8 publications

References 11 publications

Traffic Simulation in SAGIN Air Segment Containing Ad Hoc Network of Flying Drones

Traffic Simulation in SAGIN Air Segment Containing Ad Hoc Network of Flying Drones

Studying Data Loss, Nonlinearity, and Modulation Effects in Drone Swarms with Artificial Intelligence

Modeling of UAV/RPAS data traffic in space, air, and ground networks

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