Jul 2026· Journal of Institute of Science and Technology· Vol 31, pp. 137-148· 0 citations
TL;DR
A dynamic, three-layer radio-resource-management framework, built on the O-RAN Near-Real-Time Radio Intelligent Controller (Near-RT RIC) that meets these three conflicting SLAs concurrently on a shared gNB is designed and evaluated.
Abstract
Network slicing in 5G New Radio (NR) requires the simultaneous satisfaction of heterogeneous Service Level Agreements (SLAs) for ultra-reliable low-latency communications (uRLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC). The objective of this study is to design and evaluate a dynamic, three-layer radio-resource-management framework, built on the O-RAN Near-Real-Time Radio Intelligent Controller (Near-RT RIC) that meets these three conflicting SLAs concurrently on a shared gNB. At the data plane, three algorithms are proposed: a Weighted Proportional-Fair (WPF) scheduler that maps RIC-issued weights to proportional-fair time windows; a slice-aware pre-processor that estimates per-slice Physical Resource Block (PRB) demand; and a starvation-aware Bandwidth Part (BWP) multiplexer. At the RIC, a heuristic BWP Manager observes per-slice key performance indicators every 100 ms and updates the slice weights through an exponential-moving-average-smoothed proportional update law. The framework is implemented in ns-3 v3.40 with the 5G-LENA NR module, co-simulated with a Python RIC through ns3-gym, and compared against a static-weight TDMA-PF baseline. Preliminary results from a 10-second co-simulation, in which a single gNB serves 5 uRLLC, 10 eMBB and 30 mMTC user equipments across three independent BWPs, show that the dynamic framework attains 100% uRLLC deadline compliance (mean delay 0.49 ms), 100% eMBB throughput success (34.9 Mbps per UE) and zero mMTC packet loss, whereas the static baseline fails all three SLAs. The idealized modelling assumptions and their implications for real deployments are discussed as limitations.
Real-time inter-slice resource allocation in the Radio Access Network (RAN) is a critical control function in 5G and emerging 6G networks, where the scheduler in the Distributed Unit (DU) dynamically allocates physical resources, namely Physical Resource Blocks (PRBs), to different network slices to meet their diverse Quality of Service (QoS) requirements. To address the need for faster and more flexible radio resource management, and inspired by recent efforts to extend the O-RAN architecture with a real-time controller, we investigate slice-level PRB allocation through the lens of online learning. We formulate inter-slice scheduling as a dynamic decision problem and develop a system model that captures per-slice Service Level Agreement (SLA) requirements and throughput variations over configurable time windows, without assuming future channel knowledge. Our scheduling solution is implemented as a real-time RAN control application, in line with the O-RAN proposition for dApps that are programmable and distributed software components for fine-grained control in O-RAN DUs (O-DUs) and Centralized Units (O-CUs). The proposed approach adapts inter-slice radio resource allocations based on telemetry, with low computational complexity. Experimental results show sublinear dynamic regret, up to 85% fewer SLA violations than static baselines, and submillisecond amortized control overhead. Overall, these findings highlight dynamic-benchmark online control as a practical mechanism for real-time, SLA-aware slicing in O-RAN.
Asim Zoulkarni, C. Papagianni, Georgios Iosifidis et al.· International Mediterranean...· 0 citations
Network slicing is a key enabling technology for fifth-generation (5G) and beyond mobile networks, which enables operators to run multiple logical networks on top of common physical infrastructure while meeting heterogeneous quality-ofservice (QoS) requirements. In this paper, we summarize the design, implementation, and evaluation of a UDP-based virtual network slicing simulator modeling four slices in accordance with 3GPP service types: enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), Massive Machine-Type Communications (mMTC), and a dedicated Best Effort slice. The simulator uses real UDP sockets on localhost in a multi-threaded framework and implements separate admission control per slice, supporting three configurable resourceborrowing modes—none, full, and controlled—in which the primary slices (eMBB, URLLC, mMTC) may borrow unused capacity from the Best Effort slice when their own allocation runs out. QoS metrics including throughput, packet loss ratio, one-way delay, and jitter are collected in a thread-safe manner per slice. Experimental results under controlled borrowing (60 s, 16 nodes, 3 MB per slice, 40% borrow cap) demonstrate activation of the borrowing mechanism with nonzero borrowed-in and borrowedout values, and illustrate the trade-off between primary-slice throughput and Best Effort protection.
Sroor Habeeb Mahmood, Ali Al-Allawee· IEEE Jordan Conference on Ap...· 0 citations
The rapid evolution of beyond-5G and emerging 6G networks is driving the need for flexible, reliable, and cost-efficient virtualized Radio Access Network (vRAN) architectures capable of supporting heterogeneous services such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and Massive Machine-Type Communication (mMTC). Future disaggregated RAN systems are expected to rely heavily on network slicing, functional split flexibility, and optical x-haul infrastructures to support stringent performance, scalability, and availability requirements. In this paper, we present an integrated framework for reliable, slice-aware, and functional split-aware Virtual Network Function (VNF) placement with lightpath provisioning in disaggregated vRAN environments. The proposed approach maximizes mobile network operators'profit by jointly optimizing function placement and optical resource allocation under latency, processing, bandwidth, and availability constraints. We formulate the problem as an Integer Linear Programming (ILP) model with two variants: one that employs unshared backups and another that uses a more cost-efficient shared backup scheme. To address ILP complexity, we develop a heuristic algorithm and a Genetic Algorithm (GA)-based metaheuristic that yields near-optimal solutions in real time. Extensive evaluations on topologies up to 128 nodes show that shared backup variants yield up to 18% higher profit, while maintaining up to 5-10% lower normalized CPU usage than unshared counterparts.
Mayank Ramnani, Shasank Dixit, Sushil K. Yadav et al.· 0 citations
This paper proposes a Service Level Agreement (SLA)-aware resource allocation framework for 6G V2X slicing, realized as a Soft Actor-Critic (SAC) based xApp within the Open-Radio Access Network (O-RAN) near-realtime-RAN Intelligent Controller (near-RT-RIC). The xApp dynamically distributes radio resources across heterogeneous slices, minimizing SLA violations while considering fairness and throughput efficiency. Unlike heuristic or single-metric Deep Reinforcement Learning (DRL) methods, our design incorporates deadline awareness and service reliability directly into the reward formulation. Simulation results show that the proposed scheme consistently outperforms fixed, random, proportional, and Exponential moving Average (EMA)-based baselines, improving average packet delivery ratio (PDR), reducing mean SLA violations, and achieving a Pareto-optimal trade-off between throughput and compliance. These findings demonstrate the potential of O-RAN-native intelligent control for future 6G networks.
M. Tariq, Deepak Singh, M. Saad et al.· International Conference on...· 0 citations
A coordinated communication and computing resource management framework for O-RAN-based V2N communications and demonstrates a balanced trade-off among SLA compliance, computing-resource satisfaction, delay, throughput, and mobility robustness, while also showing that load-aware steering can provide higher aggregate SLA compliance under specific traffic distributions.
Open Radio Access Network (O-RAN) disaggregates the traditional base station into the Radio Unit (RU), Distributed Unit (DU), and Central Unit (CU) with standardized open interfaces, enabling multi-vendor interoperability and reducing deployment costs. However, realizing per-flow network slicing at the DU while simultaneously meeting the high-throughput demands of 5G remains a significant challenge. This paper presents DPDK-DU-NS, a DPDK-enabled O-RAN DU that supports per-flow network slicing and bandwidth management in compliance with 3GPP 5G QoS flow and bearer management specifications. DPDK-DU-NS separates the control plane and user plane of an OpenAirInterface (OAI)-based DU and offloads user plane functions to Intel DPDK to achieve high-speed packet processing. We further propose Adaptive Metering, a dynamic bandwidth allocation mechanism that provides Guaranteed Bit Rate (GBR) service while fairly distributing residual capacity among active QoS flows, leveraging the Two-Rate Three-Color Marker (trTCM) algorithm. Experimental results demonstrate that the system enforces 3GPP-compliant per-flow bandwidth guarantees and limits with near-perfect fairness, ensuring robust network slice isolation. These findings, coupled with the achieved 10 Gbps line-rate throughput, validate the DPDK-DU-NS user plane as a high-performance and scalable foundation for next-generation O-RAN DU implementations.
