Predictive Closed-Loop Service Automation in O-RAN based Network Slicing
Samsung R&D（三星研发中心）；Virginia Tech（弗吉尼亚理工学院）；San Jose State University（圣何塞州立大学）；Manchester Metropolitan University（曼彻斯特城市大学）；MediaTek（联发科）
Joseph Thaliath, Solmaz Niknam, Sukhdeep Singh, Rahul Banerji, Navrati Saxena, Harpreet S. Dhillon, Jeffrey H. Reed, Ali Kashif Bashir, Avinash Bhat, Abhishek Roy
Network slicing provides introduces customized and agile network deployment for managing different service types for various verticals under the same infrastructure. To cater to the dynamic service requirements of these verticals and meet the required quality-of-service (QoS) mentioned in the service-level agreement (SLA), network slices need to be isolated through dedicated elements and resources. Additionally, allocated resources to these slices need to be continuously monitored and intelligently managed. This enables immediate detection and correction of any SLA violation to support automated service assurance in a closed-loop fashion. By reducing human intervention, intelligent and closed-loop resource management reduces the cost of offering flexible services. Resource management in a network shared among verticals (potentially administered by different providers), would be further facilitated through open and standardized interfaces. Open radio access network (O-RAN) is perhaps the most promising RAN architecture that inherits all the aforementioned features, namely intelligence, open and standard interfaces, and closed control loop. Inspired by this, in this article we provide a closed-loop and intelligent resource provisioning scheme for O-RAN slicing to prevent SLA violations. In order to maintain realism, a real-world dataset of a large operator is used to train a learning solution for optimizing resource utilization in the proposed closed-loop service automation process. Moreover, the deployment architecture and the corresponding flow that are cognizant of the O-RAN requirements are also discussed.
Network slicing is one of the key features for 5G networks to be able to accommodate the anticipated diversity of applications and business actors in a resource-efficient manner. While significant progress has already been achieved at 3GPP specifications level with regard to the system architectural and functional aspects for the realisation of network slicing in 5G networks, management solutions for the exploitation of this feature in the Next Generation Radio Access Network (NG-RAN) are still at a very incipient stage. In this context, this paper presents a framework for the management of ne…
Driven by closed-loop automation, the Zero-Touch Network and Services Management (ZSM) framework offers invigorating features for the end-to-end management and orchestration of a sliced network. Although ZSM is considered a promising framework by 3GPP, there is a lack of concrete ZSM-based solutions for the 3GPP Network Slicing management. This article presents an architectural framework of a ZSM-based management system for 3GPP Network Slicing. The proposed framework employs recursive ZSM management domains to meet the specific management requirements of the standard 3GPP Network Slicing fram…
5G technology complements the enabling of communication services for different vertical industries such as smart distribution grids. Automation is an integral and necessary part of the power distribution grid operation and management. This paper postulates a framework by which the smart distribution grid can obtain service-oriented communication services using 5G network slicing and intent-based networking (IBN). IBN provides an interface to service users and network stakeholders to cooperate through a high level abstraction model of service provisioning in a network agnostic manner. The autom…
Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing
Iquadrat Informatica S.L.（伊夸德拉特信息有限公司）；Technical University of Catalonia (UPC)（加泰罗尼亚理工大学）；i2CAT Foundation（i2CAT基金会）；ATHENA/ISI（雅典娜信息系统研究所）；University of Patras（帕特雷大学）
Artificial intelligence (AI)-driven zero-touch network slicing (NS) is a new paradigm enabling the automation of resource management and orchestration (MANO) in multi-tenant beyond 5G (B5G) networks. In this paper, we tackle the problem of cloud-RAN (C-RAN) joint slice admission control and resource allocation by first formulating it as a Markov decision process (MDP). We then invoke an advanced continuous deep reinforcement learning (DRL) method called twin delayed deep deterministic policy gradient (TD3) to solve it. In this intent, we introduce a multi-objective approach to make the central…
Artificial intelligence (AI)-driven zero-touch network slicing is envisaged as a promising cutting-edge technology to harness the full potential of heterogeneous 5G and beyond 5G (B5G) communication systems and enable the automation of demand-aware resource management and orchestration (MANO). In this paper, we tackle the issue of B5G radio access network (RAN) joint slice admission control and resource allocation according to proposed slice-enabling cell-free massive multiple-input multiple-output (mMIMO) setup by invoking a continuous deep reinforcement learning (DRL) method. We present a no…
The evolution of the future beyond-5G/6G networks towards a service-aware network is based on network slicing technology. With network slicing, communication service providers seek to meet all the requirements imposed by the verticals, including ultra-reliable low-latency communication (URLLC) services. In addition, the open radio access network (O-RAN) architecture paves the way for flexible sharing of network resources by introducing more programmability into the RAN. RAN slicing is an essential part of end-to-end network slicing since it ensures efficient sharing of communication and comput…
To meet the diverse demands for wireless communication, fifth-generation (5G) networks and beyond (B5G) embrace the concept of network slicing by forging virtual instances (slices) of its physical infrastructure. While network slicing constitutes dynamic allocation of core network and radio access network (RAN) resources, this article emphasizes RAN slicing (RAN-S) design. Forming on-demand RAN-S that can be flexibly (re)-configured while ensuring slice isolation is challenging. A variety of machine learning (ML) techniques have been recently introduced for traffic forecasting and classificati…
Network slicing is considered a key mechanism to serve the multitude of tenants (e.g. vertical industries) targeted by forthcoming 5G systems in a flexible and cost-efficient manner. In this paper, we present a SDN/NFV architecture with multi-tenancy support. This architecture enables a network slice provider to deploy network slice instances for multiple tenants on-the-fly, and simultaneously provision them with isolation guarantees. Following the Network Slice as-a-Service delivery model, a tenant may access a Service Catalog, selecting the slice that best fits its needs and ordering its dep…
University of Waterloo（滑铁卢大学）；Huawei Technologies Canada Inc.（华为技术加拿大公司）
In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which multiple logically-isolated slices are constructed on a common roadside network infrastructure. A dynamic RAN slicing framework is presented to dynamically allocate radio spectrum and computing resource, and distribute computation workloads for the slices. To obtain an optimal RAN slicing policy for accommodating the spatial-temporal dynamics of vehicle traffic density, we first formulate a constrained RAN slicing prob…
Tactile Internet (TI) enables the omnipresence and exchange of tactile experiences across the global via the ultra-reliable and ultra-responsive connectivity. This article argues for coordinated multi-point (CoMP) enabled radio access network (RAN) slicing as an efficient solution that satisfies the stringent reliable and responsive connectivity requirements for supporting tactile applications. This article presents the emerging challenges when accommodating CoMP-enabled RAN slicing in the TI ecosystem and expounds the functional split of CoMP-enabled RAN. Besides, this article elaborates on t…
Recently, open radio access network (O-RAN) has become a promising technology to provide an open environment for network vendors and operators. Coordinating the x-applications (xAPPs) is critical to increase flexibility and guarantee high overall network performance in O-RAN. Meanwhile, federated reinforcement learning has been proposed as a promising technique to enhance the collaboration among distributed reinforcement learning agents and improve learning efficiency. In this paper, we propose a federated deep reinforcement learning algorithm to coordinate multiple independent xAPPs in O-RAN …
Technology Innovation Institute（技术创新研究院）；Trinity College Dublin（都柏林圣三一学院）
Network slicing is a well assessed approach enabling virtualization of the mobile core and radio access network (RAN) in the emerging 5th Generation New Radio. Slicing is of paramount importance when dealing with the emerging and diverse vertical applications entailing heterogeneous sets of requirements. 5G is also envisioning Unmanned Aerial Vehicles (UAVs) to be a key element in the cellular network standard, aiming at their use as aerial base stations and exploiting their flexible and quick deployment to enhance the wireless network performance. This work presents a UAV-assisted 5G network,…
Open radio access network (ORAN) alliance which has been formed recently establishes a flexible, open, and smart radio access network (RAN) by combing the ideas from xRAN and cloud RAN (C-RAN). ORAN divides the functions of the RAN into three parts, namely remote unit (RU), distributed unit (DU), and central unit (CU). While RU contains lower PHY functions, DU contains higher PHY, MAC, and RLC and CU contains RRC, PDCP, and SDAP. CU and DU are implemented as virtual network functions (VNFs) running on a cloud environment. Interface between RU, CU, and DU are open standard interfaces. Network s…
5G radio access network (RAN) with network slicing methodology plays a key role in the development of the next-generation network system. RAN slicing focuses on splitting the substrate's resources into a set of self-contained programmable RAN slices. Leveraged by network function virtualization (NFV), a RAN slice is constituted by various virtual network functions (VNFs) and virtual links that are embedded as instances on substrate nodes. In this work, we focus on the following fundamental tasks: i) establishing the theoretical foundation for constructing a VNF mapping plan for RAN slice recov…
Radio access network (RAN) slicing realizes a vision where physical network resources that belong to a specific infrastructure provider can be shared among multiple mobile network operators (MNOs). Existing work in this area has addressed RAN slicing at different levels of network abstractions, but has often neglected the multitude of tightly intertwined inter-level operations involved in real-world slicing systems. For this reason, this article discusses a novel framework for operator-to-waveform 5G RAN slicing. In the proposed framework, slicing operations are treated holistically, including…
Future wireless networks are envisioned to serve massive Internet of things (mIoT) via some radio access technologies, where the random access channel (RACH) procedure should be exploited for IoT devices to access the networks. However, the theoretical analysis of the RACH procedure for massive IoT devices is challenging. To address this challenge, we first correlate the RACH request of an IoT device with the status of its maintained queue and analyze the evolution of the queue status. Based on the analysis result, we then derive the closed-form expression of the random access (RA) success pro…
End-to-End (E2E) network slicing enables wireless networks to provide diverse services on a common infrastructure. Each E2E slice, including resources of radio access network (RAN) and core network, is rented to mobile virtual network operators (MVNOs) to provide a specific service to end-users. RAN slicing, which is realized through wireless network virtualization, involves sharing the frequency spectrum and base station antennas in RAN. Similarly, in core slicing, which is achieved by network function virtualization, data center resources such as commodity servers and physical links are shar…
Network slicing is a fundamental feature of 5G systems to partition a single network into a number of segregated logical networks, each optimized for a particular type of service, or dedicated to a particular customer or application. The realization of network slicing is particularly challenging in the Radio Access Network (RAN) part, where multiple slices can be multiplexed over the same radio channel and Radio Resource Management (RRM) functions shall be used to split the cell radio resources and achieve the expected behaviour per slice. In this context, this paper describes the key design a…
Politecnico di Bari（巴里理工大学）；Università degli Studi di Siena（锡耶纳大学）；Università degli Studi di Pisa（比萨大学）；CNIT, Consorzio Nazionale Interuniversitario per le Telecomunicazioni（意大利国家电信大学间联盟（CNIT））
The combination of cloud computing capabilities at the network edge and artificial intelligence promise to turn future mobile networks into service- and radio-aware entities, able to address the requirements of upcoming latency-sensitive applications. In this context, a challenging research goal is to exploit edge intelligence to dynamically and optimally manage the Radio Access Network Slicing (that is a less mature and more complex technology than fifth-generation Network Slicing) and Radio Resource Management, which is a very complex task due to the mostly unpredictably nature of the wirele…
Towards Bridging the FL Performance-Explainability Trade-Off: A Trustworthy 6G RAN Slicing Use-Case
Iquadrat Informatica（伊夸德拉特信息公司）；Universitat Politècnica de Catalunya (UPC)（加泰罗尼亚理工大学）；i2CAT Foundation（i2CAT基金会）；University of Patras（帕特雷大学）；ISI/ATHENA（雅典娜创新基金会信息研究所）
A significant purpose of 5G networks is allowing sharing resources among different network tenants such as service providers and Mobile Virtual network Operators. Numerous domains are taken in account regarding resource sharing containing different infrastructure (storage, compute and networking), Radio Access Network (RAN) and Radio Frequency (RF) spectrum. RAN and spectrum, transport. Spectrum sharing and RAN are anticipated as the fundamental part in multi-tenant 5G network. Nevertheless, there is a shortage of evaluation platforms to determine the number of benefits that can be acquired fr…
University of South Florida（南佛罗里达大学）；Electrical Engineering Department, University of South Florida（南佛罗里达大学电气工程系）；University of South Florida, Tampa, FL 33620, USA（南佛罗里达大学，美国佛罗里达州坦帕市，邮编33620）
Intelligent vehicular systems and smart city applications are the fastest growing Internet of things (IoT) implementations at a compound annual growth rate of 30%. In view of the recent advances in IoT devices and the emerging new breed of IoT applications driven by artificial intelligence (AI), fog radio access network (F-RAN) has been recently introduced for the fifth generation (5G) wireless communications to overcome the latency limitations of cloud-RAN (C-RAN). We consider the network slicing problem of allocating the limited resources at the network edge (fog nodes) to vehicular and smar…
An efficient resource management scheme is critical to enable network slicing in 5G networks and in envisioned 6G networks, and artificial intelligence (AI) techniques offer promising solutions. Considering the rapidly emerging new machine learning techniques, such as graph learning, federated learning, and transfer learning, a timely survey is needed to provide an overview of resource management and network slicing techniques of AI-enabled wireless networks. This article provides such a survey along with an application of knowledge transfer in radio access network (RAN) slicing. In particular…
The emerging 5G technology needs to support simultaneously running incompatible service types on a common infrastructure. Network slicing is a solution that corresponds a slice of the network to each service type. Ensuring that user activity in one slice does not affect other slices, i.e., inter-slice isolation, is a key requirement of slicing. Since due to interference and channel conditions, wireless link quality is unpredictable and variable, providing isolation in radio access network (RAN) is cumbersome. In this technical report, we consider multi-cell RAN slicing where the coupled interf…
5G radio access network (RAN) slicing aims to logically split an infrastructure into a set of self-contained programmable RAN slices, with each slice built on top of the underlying physical RAN (substrate) is a separate logical mobile network, which delivers a set of services with similar characteristics. Each RAN slice is constituted by various virtual network functions (VNFs) distributed geographically in numerous substrate nodes. A key challenge in building a robust RAN slicing is, therefore, designing a RAN slicing (RS)-configuration scheme that can utilize information such as resource ava…
Network slicing is a critical technique for 5G communications that covers radio access network (RAN), edge, transport and core slicing.The evolving network architecture requires the orchestration of multiple network resources such as radio and cache resources. In recent years, machine learning (ML) techniques have been widely applied for network management. However, most existing works do not take advantage of the knowledge transfer capability in ML. In this paper, we propose a deep transfer reinforcement learning (DTRL) scheme for joint radio and cache resource allocation to serve 5G RAN slic…
Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared to the social optimum, and demonstrate that the PoA is upper-bounded by 3…
Network slicing envisions the 5th generation (5G) mobile network resource allocation to be based on different requirements for different services, such as Ultra-Reliable Low Latency Communication (URLLC) and Enhanced Mobile Broadband (eMBB). Open Radio Access Network (O-RAN), proposes an open and disaggregated concept of RAN by modulizing the functionalities into independent components. Network slicing for O-RAN can significantly improve performance. Therefore, an advanced resource allocation solution for network slicing in O-RAN is proposed in this study by applying Reinforcement Learning (RL…
To implement network slicing in 5G, resource allocation is a key function to allocate limited network resources such as radio and computation resources to multiple slices. However, the joint resource allocation also leads to a higher complexity in the network management. In this work, we propose a knowledge transfer based resource allocation (KTRA) method to jointly allocate radio and computation resources for 5G RAN slicing. Compared with existing works, the main difference is that the proposed KTRA method has a knowledge transfer capability. It is designed to use the prior knowledge of simil…
The notions of softwarization and virtualization of the radio access network (RAN) of next-generation (5G) wireless systems are ushering in a vision where applications and services are physically decoupled from devices and network infrastructure. This crucial aspect will ultimately enable the dynamic deployment of heterogeneous services by different network operators over the same physical infrastructure. RAN slicing is a form of 5G virtualization that allows network infrastructure owners to dynamically "slice" and "serve" their network resources (i.e., spectrum, power, antennas, among others)…
The ever increasing number of connected devices and of new and heterogeneous mobile use cases implies that 5G cellular systems will face demanding technical challenges. For example, Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) scenarios present orthogonal Quality of Service (QoS) requirements that 5G aims to satisfy with a unified Radio Access Network (RAN) design. Network slicing and mmWave communications have been identified as possible enablers for 5G. They provide, respectively, the necessary scalability and flexibility to adapt the network to each …
The coexistence of diverse services with heterogeneous requirements is a fundamental feature of 5G. This necessitates efficient radio access network (RAN) slicing, defined as sharing of the wireless resources among diverse services while guaranteeing their respective throughput, timing, and/or reliability requirements. In this paper, we investigate RAN slicing for an uplink scenario in the form of multiple access schemes for two user types: (1) broadband users with throughput requirements and (2) intermittently active users with timing requirements, expressed as either latency-reliability (LR)…
Virginia Tech（弗吉尼亚理工大学）；Intelligent Automation, Inc.（智能自动化公司）
The paper presents a reinforcement learning solution to dynamic resource allocation for 5G radio access network slicing. Available communication resources (frequency-time blocks and transmit powers) and computational resources (processor usage) are allocated to stochastic arrivals of network slice requests. Each request arrives with priority (weight), throughput, computational resource, and latency (deadline) requirements, and if feasible, it is served with available communication and computational resources allocated over its requested duration. As each decision of resource allocation makes s…
As progressive densification of cells, deployment of Cloud-RAN and \ac{MEC} are coming into reality to support the ultra-low latency with high reliability in 5G and beyond, it generates mesh traffic pattern across fronthaul network. This led to evolution of PON architectural enhancements with virtualization in order to support such mesh traffic pattern. However, allocation of virtual PON slices dynamically over such mesh-PON based fronthaul transport is becoming a research challenge. In this paper, we provide a mixed analytical-iterative model to compute optimal virtual PON slice allocation, p…
