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The study presents the development and verification of an adaptive data transmission system for controlling unmanned surface vehicles (USVs) in unstable communication channels. The work aims to overcome the limitations of existing technologies, which include LTE networks and satellite s...
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| author | Kurdiuk, Sergiy Melnyk, Oleksiy Onishchenko, Oleg Volianskiy, Sergiy Shevchenko, Valerіі Alieksieichuk, Вogdan |
| author_facet | Kurdiuk, Sergiy Melnyk, Oleksiy Onishchenko, Oleg Volianskiy, Sergiy Shevchenko, Valerіі Alieksieichuk, Вogdan |
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| description | The study presents the development and verification of an adaptive data transmission system for controlling unmanned surface vehicles (USVs) in unstable communication channels. The work aims to overcome the limitations of existing technologies, which include LTE networks and satellite systems that fail to deliver stable service quality for USV remote control operations. The proposed adaptive routing algorithm evaluates communication channel status through three vital indicators, which include delay, packet loss, and availability. The algorithm selects the best channels according to changing weight parameters. Experimental results confirmed a significant reduction in data transmission delays, stable real-time video streaming with a delay of 1–4 seconds, and a reduction in packet loss to below 2 %. In addition, the system implements the use of modern video coding standards (e.g., H.265) and secure VPN channels, which increase bandwidth efficiency and the level of cybersecurity. The results confirm the practical suitability of the proposed system for USV operation in real marine conditions, as well as its potential for use in critical scenarios that require stable, low-latency communication. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2026.1.05 |
| first_indexed | 2026-04-20T01:00:21Z |
| format | Article |
| fulltext |
S.V. Kurdiuk, O.M. Melnyk, O.A. Onishchenko, S.M. Volianskyy, V.A. Shevchenko, В.M. Alieksieichuk, 2026
76 ISSN 1681–6048 System Research & Information Technologies, 2026, № 1
UDC 629.5.017.3:621.391
DOI: 10.20535/SRIT.2308-8893.2026.1.05
PRACTICAL ASPECTS OF CREATING A DATA TRANSMISSION
SYSTEM FOR CONTROLLING UNMANNED SURFACE
VEHICLES IN UNSTABLE COMMUNICATION CHANNELS
S.V. KURDIUK, O.M. MELNYK, O.A. ONISHCHENKO,
S.M. VOLIANSKYY, V.A. SHEVCHENKO,
В.M. ALIEKSIEICHUK
Abstract. The study presents the development and verification of an adap-
tive data transmission system for controlling unmanned surface vehicles
(USVs) in unstable communication channels. The work aims to overcome
the limitations of existing technologies, which include LTE networks and
satellite systems that fail to deliver stable service quality for USV remote
control operations. The proposed adaptive routing algorithm evaluates com-
munication channel status through three vital indicators, which include de-
lay, packet loss, and availability. The algorithm selects the best channels ac-
cording to changing weight parameters. Experimental results confirmed a
significant reduction in data transmission delays, stable real-time video
streaming with a delay of 1–4 seconds, and a reduction in packet loss to be-
low 2 %. In addition, the system implements the use of modern video coding
standards (e.g., H.265) and secure VPN channels, which increase bandwidth
efficiency and the level of cybersecurity. The results confirm the practical
suitability of the proposed system for USV operation in real marine condi-
tions, as well as its potential for use in critical scenarios that require stable,
low-latency communication.
Кeywords: adaptive data transfer, unmanned vehicles, handling, maneuver-
ing, navigation safety, communication channels, course control, routing al-
gorithm, delay optimization, loss reduction, data packets, operational effi-
ciency, status monitoring, 5G integration, predictive machine learning
models.
INTRODUCTION
Unmanned Surface Vehicles (USVs) have become widely used in various indus-
tries and defense applications. Their versatility is due to a combination of high
autonomy, navigation accuracy, and the ability to perform tasks in difficult and
potentially dangerous conditions where the use of manned vessels is economically
or safety unjustified. One of the major aspects of their efficiency is the reliance on
communication mechanisms, which provide real-time data exchange and facilitate
the distant or self-governing control functions.
Despite progress in satellite technology and wireless networks, data channels
for USVs remain vulnerable to bad weather, congested networks, and interference
in areas of heavy ship traffic, which results in delays, packet losses, and commu-
nication disconnections, significantly lowering the reliability of important opera-
tions, including video streaming, remote control, and autonomous navigation.
Thus, the development of very reliable and adaptive communication solutions is
the only way to assure the uninterrupted operation of USVs in the highly dynamic
marine locations.
Practical aspects of creating a data transmission system for controlling unmanned surface…
Системні дослідження та інформаційні технології, 2026, № 1 77
With the development of data transmission technologies and the growth of
mobile operators and satellite communications infrastructure, the need for a relia-
ble communication system to control unmanned surface vehicles in unstable data
links is increasing. Such systems are essential for efficient and secure remote con-
trol, especially when streaming live video and maintaining stable communication
with mobile objects. However, current IP networks, which were not initially de-
signed for online video transmission, face challenges such as packet loss and sig-
nificant latency. These factors critically impact broadcast quality of experience
(QoE), especially for streams compressed to modern standards such as H.265,
which depend on link stability and bandwidth.
Moreover, LTE mobile networks and satellite systems like Starlink might
run into impediments such as intermittent sporadic disconnectivity and exacerbat-
ed-latencies bursts from packet transmissions. In the backdrop of a situation of
uncertainty, whereby perhaps signals from mobile companies would be erratic,
and where amplitude variations on the dish would disallow constant quality in the
provision of digital services; this situation would necessitate ad-hoc channel hop-
ping solutions to ensure video transmission is successfully spread across channels
with the least possible latency.
Current research principally focuses more on improving network variables or
increasing the stability of individual links in the com-mon mesh scenario. Not
much of the work has been directed at the design on a routing-system based on
multiple adaptive channels for UAVs which consider their environmental dynam-
ic nature. In the sense of technical overhand, this article attempts to fill in that
space by introducing a new algorithm offers an absolute optimization for ad-hoc
transmission of data.
RELATED WORK
The current approaches to maintaining quality of communication with unmanned
surface vehicles (USVs) on unstable data links include a wide range of techniques to
minimize latency, packet loss, and link resilience. Previous research in USV com-
munication can be categorized into three main areas: signal and interference robust-
ness, adaptive algorithms for dynamic environments, and multi-channel approaches
for fault tolerance. This categorization allows us to identify the gaps the proposed
research aims to address.
In 2023, 3GPP presented an overview of support for the NR (New Radio)
standard for USVs, emphasizing the adaptation of modern networks for seamless
data transmission and control in a multi-channel network environment [1]. However,
current technologies are under-researched in terms of adaptive channel selection un-
der dynamic network variability, which requires further development of algorithms
that can take into account the parameters of current network conditions to improve
quality of service (QoS) and quality of experience (QoE) perception.
Research in video streaming emphasizes the critical impact of packet loss and
delay variations on real-time quality. In [2], they considered how delay and packet
loss variations reduce the QoE perception, which is especially relevant for USV
streaming, where delays can become critical for the operator. Other works, such as
[3], have proposed a QoE prediction model for multimedia services but have not
provided an adaptive solution capable of dynamically adjusting to changes in net-
work conditions. In contrast, [4] proposed an approach to improve QoE in wireless
S.V. Kurdiuk, O.M. Melnyk, O.A. Onishchenko, S.M. Volianskyy, V.A. Shevchenko, В.M. Alieksieichuk
ISSN 1681–6048 System Research & Information Technologies, 2026, № 1 78
network conditions using multiple coding, improving data transmission reliability in
a variable bandwidth network.
The predictive and adaptive QoE control techniques for video streaming pro-
posed by [5] allow for estimating the current network parameters and adjusting the
routing parameters based on changes in transmission conditions. However, their ad-
aptation framework does not cover specialized solutions for multi-channel routing in
drone environments, where latency and packet loss during control are critical. At the
level of specific network technologies, [6, 7] discusses the importance of minimizing
control channel delay for remote control systems, showing that LTE and 4G net-
works pose significant limitations regarding stability and latency. However, their
research focuses more on theoretical estimates of delay parameters rather than the
practical use of adaptive routing algorithms for continuous drone control on unstable
communication channels [8].
Routing optimization and traffic management techniques, such as the one pro-
posed in [9], offer solutions that provide fault tolerance and security to networks un-
der multi-criteria routing conditions. However, applying these solutions to un-
manned aerial vehicle (UAV) scenarios is limited because they do not provide
dynamic adaptation to real-time channel changes, which is critical for link stability
in drone control systems [10, 11]. The authors in [12] also proposed complex opti-
mization methods for self-organizing networks, which can theoretically improve
adaptive routing control, but requires refinement for practical application under high
load conditions and frequent link switching.
Based on the analysis of existing research, it can be seen that although many
approaches have been developed to improve QoE and reduce data transmission la-
tency, a significant gap remains in adaptive routing for highly loaded, unstable links
used for drone data transmission [13–16]. This study seeks to address this gap by
proposing an algorithm capable of dynamically accounting for changes in network
parameters and adjusting data routes to ensure high stability and quality of real-time
drone communications [17, 18]. Additional research offers unique approaches to
improve security and resilience in complex environments. In [19], radar-based meth-
ods for object detection and recognition on water were investigated, highlighting the
importance of reliability and accuracy of data transmission in unstable environments
similar to those observed in control. [20, 21] developed polarization-based ap-
proaches to improve object identification and safety under challenging data trans-
mission conditions applicable to tasks. In [22] investigated the energy efficiency of
motors, which can further contribute to the sustained operation of drones, especially
in environments where channel quality and reliability are critical to maintain control.
Reliable two-way communication with UAVs is critical for efficient control
and data exchange. Several studies have focused on energy efficiency and system
optimization. For example, the energy efficiency improvement of electric motors in
autonomous vehicles was investigated in [23], and energy-efficient positioning sys-
tems for multi-purpose ships were proposed in [26]. In [24], a simulation-based
method for predicting the seaworthiness of vessels applicable to UAV performance
modeling was developed, and operational efficiency in transportation projects was
evaluated [25].
Communication protocols have also been a key area of research. Shi et al. re-
viewed protocols for UAV inspections [27] and studied optimal power allocation
methods [28]. In [29], UAV swarm architecture for efficient data routing. Sources
[30–35] are devoted to current research in the field of unmanned aerial vehicles and
Practical aspects of creating a data transmission system for controlling unmanned surface…
Системні дослідження та інформаційні технології, 2026, № 1 79
marine technologies. The research focuses on designing two-way communication
systems for UAVs and optimizing secure communication through full-duplex sys-
tems and RIS technology and implementing solar power solutions on commercial
vessels for emergency fire protection. The combination of these research studies
shows progress in multiple fields which include communication protocols and cyber
security and energy sustainability and intelligent control systems.
Intelligent control systems and methods for enhancing maneuverability and op-
timizing energy consumption in transportation [36–39] are crucial for developing
practical solutions in UAV control. Data security and threat countermeasures [40,
41] are vital for ensuring sustainable communication and defense in unmanned sys-
tems. The extension of mathematical tools and intelligent approaches for dynamic
object control [42, 43] applies to UAV navigation. Threat analysis, obstacle avoid-
ance techniques, safety of cargo carriage and operator interaction [44, 45] form a
basis for creating reliable and safe UAV control systems. Sources [46–49] highlight
key aspects of unmanned aerial vehicle development: inertial navigation accuracy,
control system improvements, and spatial route optimization, demonstrating that
current research is focused on improving the reliability and efficiency of drones in
challenging operating conditions.
An analysis of existing research shows that, despite the significant number of
approaches proposed to improve quality of service (QoE) and reduce data transmis-
sion delays, there remains a significant gap in adaptive routing for highly loaded and
unstable channels used in unmanned aerial vehicle data transmission systems.
This paper attempts to address this shortcoming by developing an algorithm
that can dynamically respond to changes in network parameters and adjust infor-
mation transmission routes, ensuring high stability and quality of communication in
real time.
The proposed approach covers the transmission of control signals, telemetry,
and streaming video with minimal delays, and also implements the protection of in-
formation flows using VPN tunneling. As part of the study, experiments were con-
ducted on the selection of routers and the optimization of their parameters in order to
improve the efficiency of data transmission under conditions of unstable communi-
cation channels.
MATERIALS AND METHODS
Problem statement and system description
Modern data transmission systems for unmanned surface vehicle (USV) control re-
quire a stable connection that delivers control signals, telemetry, and streaming video.
These data types have different quality of service requirements: minimum latency and
high accuracy are critical for control signals while streaming video requires high
bandwidth and minimal packet loss to preserve image quality. The basis of the pro-
posed system is the use of two communication channels: LTE (4G) mobile networks
and Starlink satellite system. LTE provides a wide coverage area and affordable data
rates but is prone to instability in conditions of congestion or weak signal. Starlink, on
the other hand, provides a more stable connection through low-orbit satellites, but is
subject to signal fluctuations due to antenna movement and view limitations. In real-
world conditions, none of these technologies can guarantee constant quality of service
(quality of service), which requires the development of solutions that adapt to the cur-
S.V. Kurdiuk, O.M. Melnyk, O.A. Onishchenko, S.M. Volianskyy, V.A. Shevchenko, В.M. Alieksieichuk
ISSN 1681–6048 System Research & Information Technologies, 2026, № 1 80
rent state of the network. In real-world conditions, none of the existing wireless tech-
nologies can guarantee consistent Quality of Service (QoS), which necessitates the
development of adaptive solutions capable of responding to the current state of the
network. In particular, instability is observed in LTE mobile communications, espe-
cially in areas with heavy traffic or insufficient signal coverage. According to re-
search results, typical problems include connection drops and increased data trans-
mission delays. Fig. 1 shows that the time it takes to switch between channels can be
tens of seconds, which significantly complicates the stable control of unmanned sur-
face vehicles (USVs) and real-time data transmission.
Ping was selected as a universal tool for latency assessment due to its availa-
bility across all network environments. Although ICMP traffic can be depriori-
tized, our parallel measurements using UDP-based tools confirmed that ICMP
delays closely mirrored the latency experienced by video and telemetry data
(Fig. 1).
Fig. 1. Example of Ping command passing when switching between WAN links on Tel-
tonika RUT series routers
Similar problems occur with the frequency of connection checking at rout-
ers, as shown in Fig. 2. Here, we can see that the minimum connection check time
in the standard configuration of Teltonika routers is limited to 30 seconds, which
is insufficient for rapid adaptation to changing channel conditions.
Fig. 2. Connection state polling interval parameter for RUT routers
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The challenge is to design a data transmission system that minimizes laten-
cy, maintains stable transmission quality, and provides data protection. To
achieve this, the following approaches are used:
– video stream tuning using modern compression algorithms (e.g., H.265) to
reduce data volume without significant quality loss;
– VPN tunnels (e.g., based on OpenVPN or WireGuard) to encrypt transmit-
ted data and improve its security;
– adaptive data routing using algorithms for assessing the current channel
state (latency, packet loss, availability) to select the optimal channel in real-
time.
Optimize equipment settings, including IP camera and router parameters,
to coordinate bandwidth allocation, optimize encoding settings, and ensure stable
transmission.
Thus, the proposed communication system focuses on complex signal pro-
cessing to balance minimum latency, connection stability, and high data rate even
in unstable channel conditions.
VPN encryption introduced an additional latency of 20–50 ms. We opti-
mized MTU size, used hardware-accelerated encryption, and implemented fast
packet re-routing to mitigate this. WireGuard was selected over OpenVPN due to
its lower latency, simpler codebase, and faster handshake processes, making it
more suitable for UAV real-time communication.
Data transfer methods and technologies
Distributed multi-channel data transmission methods and adaptive routing algo-
rithms ensure stable communication with unmanned platforms even under unsta-
ble communication channel conditions. Such approaches minimize the impact of
delays, packet loss, and communication failures by distributing information flows
across multiple channels.
The developed communication system implements parallel data transmission
through various media, including mobile networks (LTE) and the Starlink satellite
system. For example, control commands can be transmitted via LTE, while video
streams can be transmitted via Starlink and this distribution increases communica-
tion reliability and reduces the risk of complete loss of communication.
In addition, dynamic traffic distribution is applied, taking into account the
current characteristics of the channels, such as bandwidth and latency. Switching
between channels is based on specific criteria – latency, packet loss percentage,
and channel availability.
Thus, if the delay in the LTE network exceeds the acceptable threshold (for
example, 400 ms), the system automatically redirects traffic via Starlink. To im-
prove the efficiency of the switching process, adaptive algorithms are used that
take into account the weighting coefficients of each channel, which change dy-
namically depending on its current state.
A comparative analysis of various data transmission technologies has shown
that the use of outdated communication standards, in particular 2G and GPRS, is
accompanied by significant signal delays – from 124 to 2819 ms, which effective-
ly makes it impossible to use them for tasks that require real-time data processing
(Fig. 3).
S.V. Kurdiuk, O.M. Melnyk, O.A. Onishchenko, S.M. Volianskyy, V.A. Shevchenko, В.M. Alieksieichuk
ISSN 1681–6048 System Research & Information Technologies, 2026, № 1 82
Fig. 3. Ping delays when modems operate in 2G and GPRS modes
In contrast, modern LTE modems that support channel aggregation signifi-
cantly increase bandwidth. Fig. 4 shows that using an LTE Сat.6 modem allows
you to combine 15 MHz and 10 MHz bands for a total channel width of up to 25
MHz. This improves link reliability and data transfer rates, especially for video
streaming.
Fig. 4. Example of using channel aggregation (CA Band) on LTE Cat.6
Distributed data transmission and adaptive routing techniques allow optimal
utilization of available communication channels, reducing latency and improving
data transmission stability. This is especially important for drone control, where
communication quality is critical to mission performance. The illustrations illus-
trate the advantages of modern data transmission technologies and the need to
abandon outdated standards.
Adaptive channel selection algorithm
An adaptive routing algorithm ensures stable communication under unstable
channel conditions by dynamically analyzing channel state and adjusting their
priorities based on current parameters. The algorithm takes into account the fol-
lowing key indicators (Table 1).
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Table 1. Key metrics used in the adaptive channel selection algorithm and their impact
on prioritization
Metric Description Impact on Priority
Latency
(Ping)
Measures the average response time of pack-
ets for each channel. If latency exceeds 400
ms, the channel receives a lower priority
Higher latency de-
creases the channel’s
priority
Packet Loss
Tracks the percentage of lost packets on each
channel. Channels with high packet loss are
excluded from routing or assigned penalty
coefficients
High packet loss re-
sults in reduced prior-
ity or exclusion from
routing
Channel
Availability
Assesses the availability of the connection. If
the channel is temporarily unavailable, its
priority is automatically decreased
Unavailable channels
are deprioritized or
excluded
Weight
Coefficients
Dynamically adjusted based on the channel’s
performance. Channels with low latency and
minimal packet loss receive the highest prior-
ity
Optimized channels
are prioritized based
on their performance
metrics
The logic of the algorithm is as follows:
1. Initialization. The initial channel weights are set (e.g., W1 = 3, W2 = 4,
W3 = 5).
2. Checking packet losses. If the losses exceed the acceptable threshold,
a penalty factor (e.g., +20) is added to the channel weight.
3. Checking the delay. If the delay is within the threshold, the channel is
checked further; if the delay is above the threshold, a penalty factor (+10) is add-
ed to the weight.
4. Channel selection. The channel with the lowest penalty (highest priority)
is selected from the available ones.
Fig. 5 shows the block diagram of the adaptive channel selection algorithm.
It includes the following steps:
initial initialization of parameters;
packet loss analysis on the channel;
ping delay verification;
dynamic change of weighting coefficients;
selection of the optimal channel for routing.
The advantage of this approach is that using this algorithm allows for reduc-
ing the switching time between channels. Minimize data loss in unstable condi-
tions and Provide reliable traffic routing for drone control tasks.
The algorithm, in turn, can be implemented as a software script to run on
routers that support dynamic routing, such as MikroTik devices. Its flexibility al-
lows it to adapt to real-time network changes, making it a versatile solution for
data communication systems.
S.V. Kurdiuk, O.M. Melnyk, O.A. Onishchenko, S.M. Volianskyy, V.A. Shevchenko, В.M. Alieksieichuk
ISSN 1681–6048 System Research & Information Technologies, 2026, № 1 84
Fig. 5. Block diagram of the data link state quality assessment algorithm for traffic routing
Experimental validation and results
The experimental results confirm the effectiveness of the proposed methods
for adaptive control of data links. The main objectives of the tests included reduc-
ing latency, improving link stability, and improving link capacity. Prior to system
optimization, significant data transmission quality problems were observed.
Fig. 6 shows an example of unoptimized traffic where high latency and ir-
regular link failures resulted in unstable network performance. Under high load
conditions, packet losses reached up to 15–20%, making it impossible to control
the drone in real time steadily.
Fig. 6. Example of data traffic values with non-optimized IP camera settings
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Significant improvements were observed after the implementation of adap-
tive channel selection algorithms. Fig. 7 demonstrates the optimized Ping latency
values, which have been reduced to 50–150 ms. This meets real-time require-
ments and ensures reliable control of the USV. Packet loss was minimized to less
than 2%, confirming the effectiveness of adaptive routing.
Fig. 7. Ping delay values in installed communication channels after implementation of
recommendations and optimization of equipment settings
The results of the experiments showed the following:
1. Delay reduction on all channels was reduced by 60–70% on average,
which ensured stable connection;
2. Stability improvement as the use of adaptive algorithms allowed to main-
tain stable data transmission even in conditions of high network load;
3. Optimization of throughput capacity. Due to dynamic routing, the load
was evenly distributed between the channels, reducing the congestion of individu-
al network segments.
These results confirm that implementing the proposed methodology of adap-
tive channel selection and equipment optimization can provide high-quality com-
munication in drone control systems. These improvements prepare the system for
real-world applications where link stability and minimum latency are critical.
RESULTS AND DISCUSSION
The study’s results confirmed the effectiveness of the proposed adaptive routing
system for data transmission in USV’s control systems. The main achievements
are significantly reducing data transmission delays, ensuring stable communica-
tion even under unstable network conditions, and minimizing packet loss. During
S.V. Kurdiuk, O.M. Melnyk, O.A. Onishchenko, S.M. Volianskyy, V.A. Shevchenko, В.M. Alieksieichuk
ISSN 1681–6048 System Research & Information Technologies, 2026, № 1 86
the experiments, it was possible to achieve video transmission with a delay of 1 to
4 seconds, corresponding to real-time requirements. The adaptive routing system
proved its ability to dynamically select the optimal channel based on current net-
work parameters such as latency, packet loss, and link availability. The fast
switching between channels maintained high reliability and quality of service,
making the system suitable for real-world applications. Baseline latency without
our algorithm ranged from 8 to 12 seconds due to frequent retransmissions and
unstable routing. Achieving 1–4 seconds with our adaptive routing is optimal for
UAV operations in challenging network conditions, ensuring timely control and
acceptable video quality.
Nevertheless, the work identified areas for further improvement. For exam-
ple, it is possible to integrate channel state prediction techniques using machine
learning algorithms, allowing for advance determination of optimal routes based
on historical data and current trends. In addition, the use of modern video encod-
ing technologies, in particular H.266/VVC, allows for a significant reduction in
the amount of data transmitted without any noticeable loss of image quality. An
additional area of optimization is the use of hardware with increased computing
power, in particular routers with faster processors, which ensures more efficient
traffic processing and routing.
Analysis of video recordings showed that in the absence of a developed al-
gorithm, frame freezes, image pixelation, and increased latency due to packet loss
are observed. After implementing the algorithm, the number of missed frames is
significantly reduced, artifacts almost disappear, and the video stream remains
stable even with changing network characteristics.
The developed system can be adapted to new communication standards, in
particular 5G, which will provide higher bandwidth and minimal delays. This
makes the proposed solution flexible and suitable for integration into scalable data
transmission networks.
CONCLUSIONS
This paper presents a study aimed at the development and experimental veri-
fication of a data transmission system for controlling unmanned surface vehicles
under conditions of unstable communication channels. The main limitations of
modern communication technologies (LTE, Starlink) in their use for USV control
are investigated. Special attention is paid to the impact of latency, packet loss, and
link instability on quality of service (QoS). An algorithm that dynamically evalu-
ates the state of available communication channels based on parameters such as
delay, packet loss, and availability is proposed and described. A system of penalty
coefficients is realized, allowing to correct channels’ priority operatively.
The proposed system was tested on actual data, which showed that the use of
adaptive routing allows for significantly reduced delays (up to 1–4 seconds) and
minimized packet losses (up to less than 2%). Modern compression algorithms
(H.265) and VPN tunnels were used to improve the security of transmitted data.
This ensured more efficient utilization of channel bandwidth. A comparative
analysis has shown that the enhanced data transmission system has evidently out-
classed the non-enhanced one especially in the main indexes of connection stabil-
ity, speed, and immunity against noise. Transmission delays, packet loss, and sig-
nal fluctuations, crucial variables for a reliable command of unmanned surface
Practical aspects of creating a data transmission system for controlling unmanned surface…
Системні дослідження та інформаційні технології, 2026, № 1 87
vehicle (USV) activities, were minimized due to fine-tuning of the transmission
parameters. The proposed architecture has shown resilience against environmental
stress and channel instability, which shows its practical potential. The future di-
rection could be integration of intelligent adaptation mechanisms specifically in-
volving real-time channel status assessment in predictive machine learning mod-
els and linking next-generation communication technologies (5G) for elevating
USV communication to the next level.
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Received 07.12.2024
INFORMATION ON THE ARTICLE
Sergiy V. Kurdiuk, ORCID: 0000-0002-3165-4571, National University “Odesa Mari-
time Academy”, Ukraine, e-mail: s.kurd@ukr.net
Oleksiy M. Melnyk, ORCID: 0000-0001-9228-8459, Odesa National Maritime
University, Ukraine, e-mail: m.onmu@ukr.net
Oleg A. Onishchenko, ORCID: 0000-0002-3766-3188, National University “Odesa Mar-
itime Academy”, Ukraine, e-mail: oleganaton@gmail.com
Sergiy M. Volianskiy, ORCID: 0000-0001-7922-0441, Odesa National Maritime Univer-
sity, Ukraine, e-mail: vffogres@gmail.com
Valerіі A. Shevchenko, ORCID: 0000-0003-3229-1909, National University “Odesa
Maritime Academy”, Ukraine, e-mail: shevchenko@onma.edu.ua
Вogdan M. Alieksieichuk, ORCID: 0000-0003-1043-5174, National University “Odesa
Maritime Academy”, Ukraine, e-mail: b.alieksieichuk@gmail.com
ПРАКТИЧНІ АСПЕКТИ СТВОРЕННЯ СИСТЕМИ ПЕРЕДАВАННЯ ДАНИХ
ДЛЯ КЕРУВАННЯ БЕЗПІЛОТНИМИ НАДВОДНИМИ АПАРАТАМИ В
УМОВАХ НЕСТАБІЛЬНИХ КАНАЛІВ ЗВ’ЯЗКУ/ С.В. Курдюк, О.М. Мельник,
О.А. Онищенко, C.М. Волянський, В.А. Шевченко, Б.М. Алєксєйчук
Анотація. Представлено розроблення й верифікацію адаптивної системи пере-
давання даних для керування безекіпажними надводними апаратами (USV) в
умовах нестабільних каналів зв’язку. Працю спрямовано на подолання обме-
жень наявних технологій, зокрема мереж LTE та супутникових систем, які не
завжди забезпечують стабільну якість сервісу під час дистанційного керування
USV. Запропоновано адаптивний алгоритм маршрутизації, що здійснює дина-
Practical aspects of creating a data transmission system for controlling unmanned surface…
Системні дослідження та інформаційні технології, 2026, № 1 91
мічне оцінювання стану каналів зв’язку за ключовими показниками: затрим-
кою, втратою пакетів та доступністю — і визначає оптимальні канали з ураху-
ванням змінних вагових коефіцієнтів. Експериментальні резуль-
тати підтвердили суттєве скорочення затримок передавання даних, стабільну
трансляцію відео в реальному часі із затримкою 1–4 секунди та зниження
втрат пакетів до рівня нижче 2%. Крім того, у системі реалізовано використан-
ня сучасних стандартів відеокодування (наприклад, H.265) та захищених VPN-
каналів, що підвищує ефективність використання пропускної здатності та рі-
вень кіберзахисту. Отримано результати, що підтверджують практичну прида-
тність запропонованої системи для експлуатації USV у реальних морських
умовах, а також її потенціал для застосування у критично важливих сценаріях,
які потребують стійкого зв’язку з низькою затримкою.
Ключові слова: адаптивне передавання даних, безпілотні апарати, керування,
маневрування, безпека навігації, канали зв’язку, управління процесами, алго-
ритм маршрутизації, оптимізація затримок, зменшення втрат, пакети даних,
потокове відео, операційна ефективність, моніторинг стану, стиснення H.265,
захищені VPN-тунелі, інтеграція 5G, моделі машинного навчання, прогнозу-
вання.
|
| id | journaliasakpiua-article-358070 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2026-04-20T01:00:21Z |
| publishDate | 2026 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/ce/363776ddb62c26fece3ed83da00c1cce.pdf |
| spelling | journaliasakpiua-article-3580702026-04-19T21:53:19Z Practical aspects of creating a data transmission system for controlling unmanned surface vehicles in unstable communication channels Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку Kurdiuk, Sergiy Melnyk, Oleksiy Onishchenko, Oleg Volianskiy, Sergiy Shevchenko, Valerіі Alieksieichuk, Вogdan адаптивне передавання даних безпілотні апарати керування маневрування безпека навігації канали зв’язку управління процесами алгоритм маршрутизації оптимізація затримок зменшення втрат пакети даних потокове відео операційна ефективність моніторинг стану стиснення H.265 захищені VPN-тунелі інтеграція 5G моделі машинного навчання прогнозування adaptive data transfer unmanned vehicles handling maneuvering navigation safety communication channels course control routing algorithm delay optimization loss reduction data packets operational efficiency status monitoring 5G integration predictive machine learning models The study presents the development and verification of an adaptive data transmission system for controlling unmanned surface vehicles (USVs) in unstable communication channels. The work aims to overcome the limitations of existing technologies, which include LTE networks and satellite systems that fail to deliver stable service quality for USV remote control operations. The proposed adaptive routing algorithm evaluates communication channel status through three vital indicators, which include delay, packet loss, and availability. The algorithm selects the best channels according to changing weight parameters. Experimental results confirmed a significant reduction in data transmission delays, stable real-time video streaming with a delay of 1–4 seconds, and a reduction in packet loss to below 2 %. In addition, the system implements the use of modern video coding standards (e.g., H.265) and secure VPN channels, which increase bandwidth efficiency and the level of cybersecurity. The results confirm the practical suitability of the proposed system for USV operation in real marine conditions, as well as its potential for use in critical scenarios that require stable, low-latency communication. Представлено розроблення й верифікацію адаптивної системи передавання даних для керування безекіпажними надводними апаратами (USV) в умовах нестабільних каналів зв’язку. Працю спрямовано на подолання обмежень наявних технологій, зокрема мереж LTE та супутникових систем, які не завжди забезпечують стабільну якість сервісу під час дистанційного керування USV. Запропоновано адаптивний алгоритм маршрутизації, що здійснює динамічне оцінювання стану каналів зв’язку за ключовими показниками: затримкою, втратою пакетів та доступністю — і визначає оптимальні канали з урахуванням змінних вагових коефіцієнтів. Експериментальні результати підтвердили суттєве скорочення затримок передавання даних, стабільну трансляцію відео в реальному часі із затримкою 1–4 секунди та зниження втрат пакетів до рівня нижче 2%. Крім того, у системі реалізовано використання сучасних стандартів відеокодування (наприклад, H.265) та захищених VPN-каналів, що підвищує ефективність використання пропускної здатності та рівень кіберзахисту. Отримано результати, що підтверджують практичну придатність запропонованої системи для експлуатації USV у реальних морських умовах, а також її потенціал для застосування у критично важливих сценаріях, які потребують стійкого зв’язку з низькою затримкою. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2026-03-31 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/358070 10.20535/SRIT.2308-8893.2026.1.05 System research and information technologies; No. 1 (2026); 76-91 Системные исследования и информационные технологии; № 1 (2026); 76-91 Системні дослідження та інформаційні технології; № 1 (2026); 76-91 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/358070/343997 |
| spellingShingle | адаптивне передавання даних безпілотні апарати керування маневрування безпека навігації канали зв’язку управління процесами алгоритм маршрутизації оптимізація затримок зменшення втрат пакети даних потокове відео операційна ефективність моніторинг стану стиснення H.265 захищені VPN-тунелі інтеграція 5G моделі машинного навчання прогнозування Kurdiuk, Sergiy Melnyk, Oleksiy Onishchenko, Oleg Volianskiy, Sergiy Shevchenko, Valerіі Alieksieichuk, Вogdan Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| title | Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| title_alt | Practical aspects of creating a data transmission system for controlling unmanned surface vehicles in unstable communication channels |
| title_full | Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| title_fullStr | Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| title_full_unstemmed | Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| title_short | Практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| title_sort | практичні аспекти створення системи передавання даних для керування безпілотними надводними апаратами в умовах нестабільних каналів зв’язку |
| topic | адаптивне передавання даних безпілотні апарати керування маневрування безпека навігації канали зв’язку управління процесами алгоритм маршрутизації оптимізація затримок зменшення втрат пакети даних потокове відео операційна ефективність моніторинг стану стиснення H.265 захищені VPN-тунелі інтеграція 5G моделі машинного навчання прогнозування |
| topic_facet | адаптивне передавання даних безпілотні апарати керування маневрування безпека навігації канали зв’язку управління процесами алгоритм маршрутизації оптимізація затримок зменшення втрат пакети даних потокове відео операційна ефективність моніторинг стану стиснення H.265 захищені VPN-тунелі інтеграція 5G моделі машинного навчання прогнозування adaptive data transfer unmanned vehicles handling maneuvering navigation safety communication channels course control routing algorithm delay optimization loss reduction data packets operational efficiency status monitoring 5G integration predictive machine learning models |
| url | https://journal.iasa.kpi.ua/article/view/358070 |
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