arXiv subjects

Cristiano Bonato Both

Publications and source records attributed to Cristiano Bonato Both.

11 recordsLinked to original sources

arXiv2026

Slice Agent: Identifying and Isolating Slices in Shared Open Radio Unit

Network Slice as a Service (NSaaS) is a key enabler of Beyond Fifth Generation (5G) and Sixth Generation (6G) networks, supporting next-generation applications such as extended reality (XR), immersive services, and the tactile Internet. These networks must provide native support for slice-aware services across the entire Radio Access Network (RAN), including the Radio Unit (RU), Distributed Unit (DU), Central Unit (CU), and transport segments (fronthaul, midhaul, and backhaul). However, uplink slicing identification in shared Open-RUs (O-RUs) presents a fundamental challenge because the Open-DU (O-DU) handles scheduling, and the O-RU does not inherently know which uplink data belongs to which slice. In MultiPoint-to-MultiPoint (MP2MP) fronthaul scenarios, this limitation is further exacerbated by synchronization and timing constraints, which necessitate that the O-RU process control messages and the encapsulated data be delivered with ultra-low latency. To address this issue, we propose a slicing agent embedded in the O-RU that identifies slices and segregates uplink data into slice-specific enhanced Common Public Radio Interface (eCPRI) packets. Our design employs a pipeline architecture with dedicated paths for time-sensitive, flexible slicing, enabling slice isolation and prioritization. When implemented on an Field-Programmable Gate Array (FPGA), the agent processes each packet in 2 clock cycles, supporting up to 3822 slices per slot. Experimental results validate the approach, showing its feasibility, scalability, and high-performance capabilities for real-time, slice-aware uplink processing in Beyond 5G and 6G Open RAN deployments.

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arXiv2026

NASP: Network Slice as a Service Platform for 5G Networks

With 5G's rapid global uptake, demand for agile private networks has exploded. A defining beyond-5G capability is network slicing. 3GPP specifies three core slice categories, massive Machine-Type Communications (mMTC), enhanced Mobile Broadband (eMBB), and Ultra-Reliable Low-Latency Communications (URLLC), while ETSI's Zero-Touch Network and Service Management (ZSM) targets human-less operation. Yet existing documents do not spell out end-to-end (E2E) management spanning multiple domains and subnet instances. We introduce the Network Slice-as-a-Service Platform (NASP), designed to work across 3GPP and non-3GPP networks. NASP (i) translates business-level slice requests into concrete physical instances and inter-domain interfaces, (ii) employs a hierarchical orchestrator that aligns distributed management functions, and (iii) exposes clean south-bound APIs toward domain controllers. A prototype was built by unifying guidance from 3GPP, ETSI, and O-RAN, identifying overlaps and gaps among them. We tested NASP with two exemplary deployments, 3GPP and non-3GPP, over four scenarios: mMTC, URLLC, 3GPP-Shared, and non-3GPP. The Communication Service Management Function handled all requests, underlining the platform's versatility. Measurements show that core-network configuration dominates slice-creation time (68 %), and session setup in the URLLC slice is 93 % faster than in the Shared slice. Cost analysis for orchestrating five versus ten concurrent slices reveals a 112 % delta between edge and centralized deployments. These results demonstrate that NASP delivers flexible, standards-aligned E2E slicing while uncovering opportunities to reduce latency and operational cost.

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arXiv2025

Towards a Robust Transport Network With Self-adaptive Network Digital Twin

The ability of the Network digital twin (NDT) to remain aware of changes in its physical counterpart, known as the physical twin (PTwin), is a fundamental condition to enable timely synchronization, also referred to as twinning. In this way, considering a transport network, a key requirement is to handle unexpected traffic variability and dynamically adapt to maintain optimal performance in the associated virtual model, known as the virtual twin (VTwin). In this context, we propose a self-adaptive implementation of a novel NDT architecture designed to provide accurate delay predictions, even under fluctuating traffic conditions. This architecture addresses an essential challenge, underexplored in the literature: improving the resilience of data-driven NDT platforms against traffic variability and improving synchronization between the VTwin and its physical counterpart. Therefore, the contributions of this article rely on NDT lifecycle by focusing on the operational phase, where telemetry modules are used to monitor incoming traffic, and concept drift detection techniques guide retraining decisions aimed at updating and redeploying the VTwin when necessary. We validate our architecture with a network management use case, across various emulated network topologies, and diverse traffic patterns to demonstrate its effectiveness in preserving acceptable performance and predicting quality of service (QoS) metrics under unexpected traffic variation, such as delay and jitter. The results in all tested topologies, using the normalized mean square error as the evaluation metric, demonstrate that our proposed architecture, after a traffic concept drift, achieves a performance improvement in per-flow delay and jitter prediction of at least 64% and 21%, respectively, compared to a configuration without NDT synchronization.

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arXiv2025

Network Digital Twin for Route Optimization in 5G/B5G Transport Slicing with What-If Analysis

The advent of fifth-generation (5G) and Beyond 5G (B5G) networks introduces diverse service requirements, from ultra-low latency to high bandwidth, demanding dynamic monitoring and advanced solutions to ensure Quality of Service (QoS). The transport network - responsible for interconnecting the radio access network and core networks - will increasingly face challenges in efficiently managing complex traffic patterns. The Network Digital Twin (NDT) concept emerges as a promising solution for testing configurations and algorithms in a virtual network before real-world deployment. In this context, this work designs an experimental platform with NDT in a transport network domain, synchronizing with the virtual counterpart and a recommendation system for what-if analysis, enabling intelligent decision-making for dynamic route optimization problems in 5G/B5G scenarios. Our NDT, composed of a Graph Neural Network (GNN), was evaluated across three different network topologies consisting of 8, 16, and 30 nodes. It achieved lower MAPE values for URLLC and eMBB slices, comparing latency predictions with actual latency after the solution implementation. These values indicate high accuracy, demonstrating the solution's effectiveness in generating precise insights into network performance if a particular solution were implemented.

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arXiv2022

A Tutorial on Trusted and Untrusted non-3GPP Accesses in 5G Systems -- First Steps Towards a Unified Communications Infrastructure

Fifth-generation (5G) systems are designed to enable convergent access-agnostic service availability. This means that 5G services will be available over 5G New Radio air interface and also through other non-Third Generation Partnership Project (3GPP) access networks, e.g., IEEE 802.11 (Wi-Fi). 3GPP has recently published the Release 16 that includes trusted non-3GPP access network concept and wireless wireline convergence. The main goal of this tutorial is to present an overview of access to 5G core via non-3GPP access networks specified by 3GPP until Release 16 (i.e., untrusted, trusted, and wireline access). The tutorial describes aspects of the convergence of a 5G system and these non-3GPP access networks, such as the authentication and authorization procedures and the data session establishment from the point of view of protocol stack and exchanged messages between the network functions. In order to illustrate several concepts and part of 3GPP specification, we present a basic but fully operational implementation of untrusted non-3GPP access using WLAN. We perform experiments that demonstrate how a Wi-Fi user is authorized in a 5G core and establishes user plane connectivity to a data network. Moreover, we evaluate the performance of this access in terms of time consumed, number of messages, and protocol overhead to established data sessions.

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arXiv2021

Tutorial on communication between access networks and the 5G core

Fifth-generation (5G) networks enable a variety of use cases that require differentiated connectivity, e.g., Ultra-Reliable and Low-Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine Type Communication (mMTC). To explore the full potential of these use cases, it is mandatory to understand the communication along with the 5G network segments and architecture components. User Equipment (UE), Radio Access Network (RAN), and 5G Core (5GC) are the main components that support these new network concepts and paradigms. 3rd Generation Partnership Project has recently published Release 16, including the protocols used to communicate between RANs and 5GC, i.e., Non-Access Stratum (NAS) and NG Application Protocol (NGAP). The main goal of this work is to present a comprehensive tutorial about NAS and NGAP specifications using a didactic and practical approach. The tutorial describes the protocol stacks and aspects of the functionality of these protocols in 5G networks, such as authentication and identification procedures, data session establishment, and resource allocation. Moreover, we review the message flows related to these protocols in UE and Next Generation Node B (gNodeB) registration. To illustrate the concepts presented in the tutorial, we developed the my5G Tester: a 5GC tester that implements NAS and NGAP for evaluating three open-source 5GC projects using a black-box testing methodology.

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arXiv2021

OPlaceRAN -- a Placement Orchestrator for Virtualized Next-Generation of Radio Access Network

The fifth-generation mobile evolution enables transformations on Next-Generation Radio Access Networks (NG-RAN). The RAN protocol stack is split into eight disaggregated options combined in three network units, i.e., Central, Distributed, and Radio. Besides that, further advances allow the RAN functions to be virtualized on top of general-purpose hardware, using the concept of virtualized RAN (vRAN). The Combination of NG-RAN and vRAN results in vNG-RAN, which enables the management of the disaggregated units and protocols as a set of radio functions. However, the orchestration-based placement of these radio functions is a challenging issue since the best decision can be determined by multiple constraints involving RAN disaggregation, crosshaul networks requirements, availability of computational resources, etc. This article proposes OPlaceRAN, a vNG-RAN deployment orchestrator framed within the NFV reference architecture and aligned with the Open RAN initiative. OPlaceRAN supports the dynamic placement of radio functions focusing on vNG-RAN planning and is designed to be agnostic to the placement optimization model. To validate OPlaceRAN, we developed a prototype based on up-to-date cloud-native tools to deploy RAN using containerized virtualization using the OpenAirInterface emulator and considering two distinct functional splits (options 2 and 6). The evaluation is tested as proofs-of-concept in a real computing infrastructure using two different placement solutions. Our results reveal that OPlaceRAN is an effective cloud-native solution for containerized network functions placement and agnostic to the optimization model. Additionally, OPlaceRAN is up-to-date with the most advanced vNG-RAN design and development approaches, contributing to the evolution of the fifth-generation of mobile networks.

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arXiv2021

PlaceRAN: Optimal Placement of Virtualized Network Functions in the Next-generation Radio Access Networks

The fifth-generation mobile evolution enables several transformations on Next Generation Radio Access Networks (NG-RAN). The RAN protocol stack is splitting into eight possible disaggregated options combined into three network units, i.e., Central, Distributed, and Radio. Besides that, further advances allow the RAN software to be virtualized on top of general-purpose vendor-neutral hardware, dealing with the concept of virtualized RAN (vRAN). The disaggregated network units initiatives reach full interoperability based on the Open RAN (O-RAN). The combination of NG-RAN and vRAN results in vNG-RAN, enabling the management of disaggregated units and protocols as a set of radio functions. The placement of these functions is challenging since the best decision can be based on multiple constraints, such as the RAN protocol stack split, routing paths of transport networks with restricted bandwidth and latency requirements, different topologies and link capabilities, asymmetric computational resources, etc. This article proposes the first exact model for the placement optimization of radio functions for vNG-RAN planning, named PlaceRAN. The main objective is to minimize the computing resources and maximize the aggregation of radio functions. The PlaceRAN evaluation considered two realistic network topologies. Our results reveal that the PlaceRAN model achieves an optimized high-performance aggregation level, it is flexible for RAN deployment overcoming the network restrictions, and it is up to date with the most advanced vNG-RAN design and development.

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arXiv2021

System Intelligence for UAV-Based Mission Critical with Challenging 5G/B5G Connectivity

Unmanned aerial vehicles (UAVs) and communication systems are fundamental elements in Mission Critical services, such as search and rescue. In this article, we introduce an architecture for managing and orchestrating 5G and beyond networks that operate over a heterogeneous infrastructure with UAVs' aid. UAVs are used for collecting and processing data, as well as improving communications. The proposed System Intelligence (SI) architecture was designed to comply with recent standardization works, especially the ETSI Experiential Networked Intelligence specifications. Another contribution of this article is an evaluation using a testbed based on a virtualized non-standalone 5G core and a 4G Radio Access Network (RAN) implemented with open-source software. The experimental results indicate, for instance, that SI can substantially improve the latency of UAV-based services by splitting deep neural networks between UAV and edge or cloud equipment. Other experiments explore the slicing of RAN resources and efficient placement of virtual network functions to assess the benefits of incorporating intelligence in UAV-based mission-critical services.

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arXiv2020

A softwarized perspective of the 5G networks

The main goal of this article is to present the fundamental theoretical concepts for the tutorial presented in IEEE NetSoft 2020. The article explores the use of software in the 5G system composed of the Radio Access Network (RAN) and the core components, following the standards defined by 3GPP, particularly the Release 15. The article provides a brief overview of mobile cellular networks, including basic concepts, operations, and evolution through the called `generations' of mobile networks. From a software perspective, RAN is presented in the context of 4G and 5G networks, which includes the virtualization and disaggregation concepts. A significant part of the article is dedicated to 5G networks and beyond, focusing on core, i.e., considering the Service-Based Architecture (SBA), due to its relevance and totally softwarized approach. Finally, the article briefly describes the demonstrations presented in IEEE NetSoft 2020, providing the link for the repository that has all material employed in the tutorial.

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arXiv2019

Power-Efficient Resource Allocation in C-RANs with SINR Constraints and Deadlines

In this paper, we address the problem of power-efficient resource management in Cloud Radio Access Networks (C-RANs). Specifically, we consider the case where Remote Radio Heads (RRHs) perform data transmission, and signal processing is executed in a virtually centralized Base-Band Units (BBUs) pool. Users request to transmit at different time instants; they demand minimum signal-to-noise-plus-interference ratio (SINR) guarantees, and their requests must be accommodated within a given deadline. These constraints pose significant challenges to the management of C-RANs and, as we will show, considerably impact the allocation of processing and radio resources in the network. Accordingly, we analyze the power consumption of the C-RAN system, and we formulate the power consumption minimization problem as a weighted joint scheduling of processing and power allocation problem for C-RANs with minimum SINR and finite horizon constraints. The problem is a Mixed Integer Non-Linear Program (MINLP), and we propose an optimal offline solution based on Dynamic Programming (DP). We show that the optimal solution is of exponential complexity, thus we propose a sub-optimal greedy online algorithm of polynomial complexity. We assess the performance of the two proposed solutions through extensive numerical results. Our solution aims to reach an appropriate trade-off between minimizing the power consumption and maximizing the percentage of satisfied users. We show that it results in power consumption that is only marginally higher than the optimum, at significantly lower complexity.

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