Vetoshko I. Method of Adaptive Radio Resource Scheduling and Retransmission Control for Improving the Quality of VoNR Voice Services in a 5G Network

Українська версія

Thesis for the degree of Doctor of Philosophy (PhD)

State registration number

0826U002010

Thesis Registration Form

0826U002010.pdf

Applicant for

Specialization

  • 172 - Електронні комунікації та радіотехніка

Specialized Academic Board

PhD 14052

National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»

Essay

Relevance of the topic. The rapid deployment of 5G SA networks necessitates ensuring stable Voice over New Radio (VoNR) quality. Existing resource scheduling and modulation-coding adaptation schemes, specifically the OLLA loop, primarily focus on optimizing average throughput and maintaining a target average BLER. They do not account for VoNR's strict timing requirements, leading to exceeded RTP packet delivery limits and multiple HARQ retransmissions. This creates a contradiction between the QoS context formed in the 5GC core (5QI profiles) and the actual control loop in the NG-RAN segment. The objective of the study is to reduce delay, delay variation, and packet loss rate, and to eliminate multiple transport block retransmissions to improve VoNR QoS and QoE indicators in 5G SA networks. The object of research is the process of ensuring VoNR QoS and QoE indicators in a 5G SA network at the NG-RAN level. The subject of research is the method of adaptive radio resource scheduling and control of HARQ retransmissions and target BLER level for the VoNR service. Research methods. The study employs system analysis of 3GPP standards, Markov-based mathematical modeling of radio access processes and stochastic channel dynamics, machine learning for channel prediction and modulation-coding scheme selection, and MATLAB simulation modeling to evaluate the method's QoS, QoE, and resource-energy efficiency. The scientific novelty of the obtained results consists in developing an integrated method for adaptive radio resource scheduling and control of HARQ retransmissions and target BLER to improve VoNR quality in 5G SA. The method combines machine-learning-based channel state prediction with MOS-oriented radio interface control. New results include: 1. For the first time, an integrated cross-layer method of adaptive radio resource scheduling for VoNR traffic is proposed. Unlike existing solutions, it implements a single closed control loop at the RRM and MAC layers, considering the 5GC QoS context. This forms coordinated control actions regarding resource allocation, modulation-coding scheme selection, HARQ configuration, and target BLER, ensuring QoS and QoE stabilization under non-stationary channel conditions and variable load. 2. The mathematical model of the adaptive radio resource scheduling problem is improved. Its distinction is the discrete problem formulation at RRM and MAC layers, forming the state vector based on PHY-layer indicators, HARQ statistics, and cumulative QoS metrics (including the share of delayed packets and multiple HARQ retransmissions) in a sliding time window. Channel dynamics are described by a Markov process, and the 5GC QoS context acts as a system of constraints formalizing the link between radio access parameters and service quality. 3. A mathematical model for MOS-oriented control of HARQ mechanisms and target BLER is developed. Unlike traditional methods optimizing average BLER or throughput, the integral voice quality assessment (MOS) is used as the objective function. The model provides dynamic modulation-coding selection and adaptive target BLER adjustment, considering the retransmission impact on timely RTP packet delivery. This reduces delayed packets and multiple transport block retransmissions while maintaining radio resource efficiency. The practical significance of the obtained results. The developed algorithmic solutions and software tools provide a basis for the design, configuration, and operational optimization of VoNR-enabled 5G SA networks. The proposed cross-layer method is suitable for integration into NG-RAN MAC-layer scheduling and radio resource management subsystems, complying with 5GC policies. Machine learning components and MOS-oriented modulation-coding selection are applicable for 5QI profile configuration. This reduces delayed packets and multiple HARQ retransmissions while preserving energy and resource efficiency. The MATLAB simulation model is effective for comparative algorithm analysis, pre-design evaluation of parameterization scenarios, and educational use. The conclusions serve as a practical basis for ensuring stably high voice service quality.

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Research papers

Vetoshko, I., Kravchuk, S. (2023). Possibilities of improving the voice services quality in 5G networks. Information and Telecommunication Sciences, (2), 9–16. https://doi.org/10.20535/2411-2976.22023.9-16

Ветошко, І., Кравчук, С. (2024). Структурні особливості реалізації голосових послуг VoNR в мережі мобільного зв’язку стандарту 5G. Вчені записки Таврійського національного університету імені В.І. Вернадського. Серія: Технічні науки, 35 (74)(1), 27–33. https://doi.org/10.32782/2663-5941/2024.1.1/04

Ветошко, І., Кравчук, С. (2024). Взаємодія та співіснування мереж радіодоступу LTE/NR. Вчені записки Таврійського національного університету імені В.І. Вернадського. Серія: Технічні науки, 35 (74)(3), 22–29. https://doi.org/10.32782/2663-5941/2024.3.2/03

Vetoshko, I., Kravchuk, S. (2025). Integration of machine learning-based prediction and dynamic QoS optimization into adaptive VoNR scheduling in 5G standalone networks: a simulation-based approach. Вчені записки Таврійського національного університету імені В.І. Вернадського. Серія: Технічні науки, 36 (75)(3), 42–55. https://doi.org/10.32782/2663-5941/2025.3.1/07

Vetoshko, I. (2025). Efficient resource allocation in 5G SA: impact of scheduling on GBR and non-GBR traffic. Вчені записки Таврійського національного університету імені В.І. Вернадського. Серія: Технічні науки, 36 (75)(5), 41–48. https://doi.org/10.32782/2663-5941/2025.5.1/07

Vetoshko, I., Kravchuk, S. (2025). Algorithm for enhancing voice quality in 5G Standalone via MOS-oriented dynamic link adaptation. Наукові записки Державного університету інформаційно-комунікаційних технологій, 2 (8), 127–137. https://doi.org/10.31673/2786-8362.2025.021693

Vetoshko, I., Kravchuk, S. (2023). Opportunities to improve the quality of voice services in 5G networks. In 2023 IEEE International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo) (pp. 92–96). IEEE. https://doi.org/10.1109/UkrMiCo61577.2023.10380376

Vetoshko, I., Noskov, V. (2021). Evaluation of voice transmission quality in the LTE networks. Information and Telecommunication Sciences, (2), 22–26. https://doi.org/10.20535/2411-2976.22021.22-26

Vetoshko, I. (2025). Flash calls in modern telecommunication networks: threats, challenges, and effective countermeasures. Наукові записки Державного університету інформаційно-комунікаційних технологій, 1 (7), 74–89. https://doi.org/10.31673/2786-8362.2025.014820

Vetoshko, I. (2025). Comparative evaluation of Round Robin, Proportional Fairness and ML-driven adaptive scheduling for VONR in 5G SA. Modern engineering and innovative technologies, 41 (01), 23-33. https://doi.org/10.30890/2567-5273.2025-41-01-068

Vetoshko, I., Kravchuk, S. (2023). Features of the RRC radio resource management protocol in the 5G network. International Scientific Symposium, Innovation in modern science, 2(№SGE20-012), 99–108. https://doi.org/10.30890/2709-2313.2023-20-02-012

Vetoshko, I. (2023). Ways to implement voice services in 5th generation networks. WOC World of Conferences: ІІ International scientific conference, 73–75. https://doi.org/10.5281/zenodo.7560026

Ветошко, І., Кравчук, С. (2025). Пріоритизація голосового трафіку в 5G: роль планувальників у забезпеченні QoS. У XIX міжнародна науково-технічна конференція «ПЕРСПЕКТИВИ ТЕЛЕКОМУНІКАЦІЙ» (с. 165–168). https://conferenc-journal.its.kpi.ua/article/view/332667

Ветошко, І. (2023). Відмінності в архітектурних підходах до побудови ядра мережі 5G. Міжнародна наукова конференція: технології, інструменти та стратегії реалізації наукових досліджень, 5, 153–154. https://archive.mcnd.org.ua/index.php/conference-proceeding/article/view/432/441

Ветошко, І., Кравчук, С. (2024). Методи реалізації технології передачі голосу VoNR у мережах 5G: опції для існуючих операторів. У XVIII міжнародна науково-технічна конференція «ПЕРСПЕКТИВИ ТЕЛЕКОМУНІКАЦІЙ» (с. 127–129). https://conferenc-journal.its.kpi.ua/article/view/307290

Vetoshko, I., Kravchuk, S. (2025). Network Functions Virtualisation (NFV) in 5G: current state and future prospects. Challenges and Opportunities in Modern Scientific Research: materials of the 1st International Scientific and Practical Conference, 198–202. https://isu-conference.com/wp-content/uploads/2025/02/Ivano-Frankivsk_Ukraine_19.02.25.pdf

Vetoshko, I. (2025). Countering flash calls in 4G and 5G with innovative detection and blocking techniques. У XIX міжнародна науково-технічна конференція «ПЕРСПЕКТИВИ ТЕЛЕКОМУНІКАЦІЙ» (с. 213–216). https://conferenc-journal.its.kpi.ua/article/view/332830

Ветошко, І., Кравчук, С. (2022). Реалізація голосових послуг у мережах 5-го покоління. Grail of Science, 23, 149–151. https://doi.org/10.36074/grail-of-science.23.12.2022.24

Ветошко, І., Кравчук, С. (2023). Розгортання голосових сервісів у мережах 5G. Grail of Science, 24, 278–281. https://doi.org/10.36074/grail-of-science.17.02.2023.051

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