IMPROVING RADIO FREQUENCY RESOURCE MANAGEMENT IN A SEGMENTED 5G RADIO ACCESS NETWORK

Abstract

This article examines the problem of radio frequency resource management in a
segmented 5G radio access network under conditions of limited physical resources in NR cells and
increasing heterogeneous service quality requirements. It is shown that, even with network segmentation
mechanisms in the core network, the implementation of end-to-end segmentation at the RAN level
remains a complex scientific and practical problem, since it is precisely in the radio access domain that
resources have strict physical constraints and are shared by multiple segments. Based on an analysis of
3GPP specifications and current scientific literature, it has been established that known approaches either
focus on signaling and architectural support for network slicing or are oriented toward local planning
schemes that do not fully account for the interests of network segments as independent optimization
objects. An improved adaptive multi-level method for managing radio frequency resources in a
segmented RAN is proposed, which combines control of the number of user devices in the
RRC_CONNECTED state at the network segment group level with multi-criteria allocation of resource
blocks at the RB level. Within a single algorithmic framework, planning modes based on QoS, RB
reservation, and physical carrier isolation are supported. The results of the simulation study showed that
the proposed method improves the overall SLA fulfillment rate to 0.877, compared to 0.844 for static
reservation and 0.856 for QoS-only scheduling, while maintaining high spectrum utilization and less
dynamic resource reconfiguration.
Keywords: 5G, network slicing, RAN slicing, S‑NSSAI, gNodeB, QoS, SLA, resource blocks,
RRC_CONNECTED, adaptive resource management

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