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Strategic UMTS sunset implementation in national-scale mobile networks: methodology, risks, and performance gains

Автор: Романюк Ігор

Библиографическое описание статьи для цитирования:

Романюк Ігор. Strategic UMTS sunset implementation in national-scale mobile networks: methodology, risks, and performance gains//Наука онлайн: Международный научный электронный журнал. - 2026. - №4. - https://nauka-online.com/ru/publications/technical-sciences/2026/4/03-48/

Аннотация: (English) The progressive retirement of legacy cellular technologies represents one of the most intricate operational challenges faced by contemporary mobile network operators. While the migration toward LTE and fifth-generation infrastructures has been widely documented, the methodological foundations governing the controlled sunset of earlier radio access technologies remain comparatively underexplored. In particular, the decommissioning of UMTS networks introduces a complex interplay between spectrum refarming, traffic redistribution, service continuity, and operational risk. If performed without analytical guidance, the shutdown of legacy radio layers may provoke severe congestion phenomena, localized capacity collapse, and degradation of user-perceived service quality. This study proposes a structured analytical framework for strategic UMTS sunset implementation within national-scale mobile networks. The research develops a mathematical model that conceptualizes technology retirement not as an isolated operational procedure but as a multi-stage optimization problem embedded within the broader dynamics of traffic migration and spectrum reallocation. The model integrates probabilistic risk estimation, predictive traffic forecasting, and performance-oriented optimization in order to determine the most balanced trajectory of legacy infrastructure decommissioning. To validate the analytical model, a dedicated experimental software environment was implemented in Python, enabling simulation of progressive UMTS shutdown scenarios and comparative evaluation of alternative decision strategies. The system incorporates modules for dataset preprocessing, predictive traffic modeling, iterative sunset simulation, and analytical visualization of network behavior. An openly available dataset describing cellular network performance indicators was used to construct a synthetic yet statistically plausible representation of sector-level radio conditions. Simulation results demonstrate that risk-aware sunset strategies significantly reduce the probability of network overload events while preserving higher LTE throughput levels during the transition process. In contrast, load-driven or stochastic shutdown strategies exhibit increased susceptibility to blackout conditions under heavy traffic migration scenarios. The obtained findings indicate that integrating predictive modeling and probabilistic risk assessment into sunset planning procedures enables a more stable and resource-efficient transformation of cellular infrastructures. The proposed methodological framework contributes to the emerging body of research on technological transitions in mobile networks by providing a coherent analytical approach to legacy technology retirement. Beyond its theoretical implications, the model may serve as a practical decision-support instrument for mobile operators planning large-scale spectrum refarming and infrastructure modernization initiatives.

Ключевые слова: cellular network evolution LTE capacity management network resilience radio access network planning risk-aware optimization spectrum refarming traffic migration modeling UMTS sunset

Рубрики: Технические науки

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Multi-layer optimization of GSM/UMTS/LTE networks: cluster-level and cell-level integrated approach

Автор: Романюк Ігор

Библиографическое описание статьи для цитирования:

Романюк Ігор. Multi-layer optimization of GSM/UMTS/LTE networks: cluster-level and cell-level integrated approach//Наука онлайн: Международный научный электронный журнал. - 2023. - №4. - https://nauka-online.com/ru/publications/technical-sciences/2023/4/14-19/

Аннотация: (English) The rapid coexistence of legacy and modern radio technologies has transformed contemporary cellular infrastructure into a layered communication environment where heterogeneous systems such as GSM, UMTS, and LTE operate within a shared spectral and interference space. Under these circumstances, traditional optimization techniques that treat individual base stations or isolated network segments as independent control units increasingly reveal their limitations. Fragmented parameter tuning frequently leads to local improvements that inadvertently propagate inefficiencies elsewhere in the network topology. Addressing this challenge requires analytical frameworks capable of perceiving the radio access network as an interconnected organism whose performance emerges from the collective behavior of clusters of cells rather than from the configuration of a single node. This study proposes an integrated multi-layer optimization approach that synchronizes cluster-level network analysis with cell-level parameter adjustment within a unified feedback-driven control structure. The suggested method introduces a mathematical model that simultaneously evaluates key performance indicators, including throughput, latency, resource utilization, and user-perceived service quality, while dynamically adapting operational parameters such as transmission power, antenna configuration, and load distribution across neighboring cells. Unlike conventional optimization strategies that operate within a single analytical scale, the proposed framework interweaves macro-level traffic equilibrium with micro-level radio control decisions. To investigate the practical viability of the model, a dedicated analytical software environment was developed using Python and applied to realistic signal measurements from the Cellular Network Analysis Dataset. The experimental evaluation demonstrates that the integrated optimization process enables a more balanced redistribution of network load, improves the stability of key performance indicators, and enhances overall service quality across heterogeneous radio layers. The results indicate that coupling cluster-oriented analytics with adaptive cell-level control creates a synergistic optimization effect that cannot be achieved through traditional single-layer methods. The proposed approach contributes to the ongoing development of intelligent radio access network management by offering a structured pathway toward automated optimization of heterogeneous cellular infrastructures, particularly during transitional phases where legacy technologies coexist with newer broadband systems.

Ключевые слова: cell-level parameter adaptation Cellular network optimization cluster-level optimization GSM/UMTS/LTE integration heterogeneous mobile networks multi-layer radio networks QoE-driven optimization radio access network management

Рубрики: Технические науки

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