Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.03209

Implementation of Hybrid QoS-Aware Data Radio Bearer in 5G Networks

Padmapriya Patil·Abhishek Bhattacharyya·Gudepu Venkateswarlu·Andrea Fumagalli·Koteswararao Kondepu
View original source ↗Read source document ↗Export metadata ↓

Abstract

In Fifth-Generation (5G) wireless networks, Quality of Service (QoS) flow management supports diverse applications with heterogeneous QoS requirements, including latency-sensitive and high-throughput services. 5G architectures adopt a flow based QoS framework, where QoS flows are mapped to Data Radio Bearers (DRBs) to achieve the desired radio resource allocation. Existing mapping strategies typically rely on static one-to-one QoS-to-DRB mappings per PDU session, leading to inefficient spectrum utilization or inadequate support for delay sensitive traffic. This work presents a hybrid QoS-aware DRB mapping mechanism based on standardized 5G QoS Identifier (5QI) characteristics. The proposed framework incorporates multiple QoS flows within a single PDU session, supporting both many-to-one and one-to-one mapping strategies. The hybrid framework improves radio resource utilization and reduced bearer overhead by enabling flexible DRB utilization, where compatible non critical flows share DRBs while delay-critical flows are assigned dedicated DRBs to ensure strict QoS guarantees. The proposed hybrid QoS-aware DRB mapping is implemented using the open-source OpenAirInterface (OAI) mobile stack platform to demonstrate the integration of the proposed features within the existing 5G framework.

Explore related subjects

cs.ET

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Padmapriya Patil, Abhishek Bhattacharyya, Gudepu Venkateswarlu, Andrea Fumagalli, Koteswararao Kondepu. 2026-10-02. Implementation of Hybrid QoS-Aware Data Radio Bearer in 5G Networks. https://arxiv.org/abs/2610.03209

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Hybrid Classical-Quantum Solutions to Accelerate the Adoption of Quantum Computing

Despite the promise and potential of quantum computing, most of the current day developments of quantum computing have several limitations for relevant practical use. As a result, hybrid classical-quantum computing has emerged as a viable solution. This paper discusses the software aspects of hybrid classical-quantum computing solutions to understand and examine how hybrid computing solutions can be expected to work in practice. This paper examines existing software solutions (cloud applications, middleware frameworks, and API gateways) that can enable classical and quantum computing to work together. For practitioners the paper provides a curated list of algorithms, full stack libraries, simulators, and cloud service providers that are likely to be central to the development of any hybrid computing solutions. We conclude by identifying an agenda for future research on classical-quantum hybrid software engineering, and some near-term priorities for development of functional, robust hybrid software systems. The paper argues that due to the deep dependency of quantum execution on classical pre- and post-processing, hybrid computing may represent a near-permanent outcome of classical-quantum computing rather than a transitional workaround.

cs.ET↗
arXiv2026

Task-Adaptive Physical Reservoir Computing via Tunable Molecular Communication Dynamics

Diffusion-based molecular communication (MC) channels suffer from two impairments: a fading channel memory from diffusion and the saturating, nonlinear dose response of ligand receptors. These impairments have been shown to enable the channel to serve as a physical reservoir computer, with memory and nonlinearity set by channel parameters that living cells already regulate. Since computing tasks require different balances of memory and nonlinearity, this paper investigates whether these parameters can tune the MC channel to different tasks, even when only some are adjustable. Bayesian optimization of a mean-field model of the MC channel reveals that the optimal configurations of three benchmark tasks, i.e., time-series forecasting, sine-to-square transformation, and their hybrid, differ in receptor operating point, timescale, and diffusion memory. Tuning the receptor kinetics alone yields most of the error reduction of tuning all parameters, while reusing a task-specific configuration across tasks incurs a penalty despite readout retraining. A stochastic receptor model shows that receptor noise penalizes memory-demanding tasks more than threshold-like ones, and that time-averaging readouts recover much of this loss. Lastly, a synthetic glucose case study demonstrates that a single channel can be switched during operation from forecasting the glucose level to detecting threshold crossings within tens of symbols.

cs.ET↗
arXiv2026

A FeFET Voltage-to-Time Converter with Offset Trim by Programmed Multilevel State in 28-nm CMOS

The offset and gain of voltage-to-time converters (VTCs) in time-domain circuits vary with process, supply, and temperature. This work presents a VTC whose nonvolatile input-referred offset trim is the programmed multilevel state of the ferroelectric field-effect transistor (FeFET) that converts the input. Fabricated in 28-nm CMOS, the 6.07-$μ$m$^2$ VTC consists of a current-starved inverter with the FeFET and a parallel NMOS leaker in its tail, a capacitor bank, and a following inverter. The programmed state shifts the transfer curve onto the input range, leaving the gain to the capacitor bank and the leaker bias. Measured at 10~MS/s, centered states weaken the second harmonic from $-$12.5~dB in the low-threshold state to $-$32.2~dB and lower the static integral nonlinearity (INL) at 5~bit from 2.42 to 0.92~LSB. Post-layout simulations indicate that the proposed VTC can operate at 500~MS/s, drawing 2.0~$μ$W from a 0.9-V supply, with nearly unchanged distortion and gain up to 700~MS/s. Across simulated process corners and $\pm$10\,\% supply variation, the input-referred offset is calibrated to within 10~mV and the gain to within 4\,\% of nominal by adjusting the programmed state and leaker bias.

cs.ET↗