Impact of CoMP VNF Placement on 5G Coordinated Scheduling Performance

To address demanding requirements in terms of expected throughput, latency and scalability, 5G networks will offer high capacity to support huge volumes of traffic generated by heterogeneous services. Dense deployment of small cells can provide a valid solution but are prone to high levels of interference especially at the cell-edge. However, to reduce inter-cell interference and improve cell-edge throughput, a set of techniques known as Coordinated Multipoint (CoMP) has been introduced. Coordinated Scheduling (CS) is a CoMP technique that assigns resources to mobile users to avoid interference between users that are assigned within the same Physical Resource Blocks (PRBs). On the other hand, Software Defined Mobile Networking (SDMN) and Network Function Virtualization (NFV) represent two key technologies to enhance flexibility and efficiency of resource usage within the Radio Access Network (RAN). However, the implementation of CoMP CS techniques on NFV architecture in a dense small cell scenario have not been analyzed yet. In this paper, we propose the joint use of CoMP CS and NFV by studying the implications of different deployment strategies, as constrained by the physical topology of the underlying RAN. The performance of both distributed and centralized CoMP CS are compared in terms of convergence delay and traffic overhead. Guidelines for the optimal design are provided.This work was partially supported by the Italian Government under CIPE resolution no. 135 (December 21, 2012), project INnovating City Planning through Information and Communication Technologies (INCIPICT) and by the EC through the H2020 5G-TRANSFORMER project (Project ID 761536)

Network Solutions for CoMP Coordinated Scheduling

Demanding throughput, latency and scalability requirements of 5G networks may be addressed by relying on dense deployments of small cells. Coordinated Multipoint (CoMP) Coordinated Scheduling (CS) techniques are introduced to reduce inter-cell interference in case of dense deployment, given that local CoMP-CS information from the evolved NodeBs (eNodeBs) in the cluster are timely collected at the scheduling decision entity. This work studies how the distribution of CoMP-CS cell information is affected by the backhaul infrastructure in terms of both physical and logical topology. The differentiation between physical and logical infrastructure is justified in the context of new approaches like Software Defined Networking and Network Function Virtualization that enable the dynamic configuration of the network. We consider either a Packet Switched Network with three possible topologies (namely, ring, mesh and star) or a Time Division Multiplexing Passive Optical Network (TDM-PON), both carrying heterogeneous traffic. To improve the convergence time in the TDM-PON, we propose a novel bandwidth allocation scheme to prioritize the signaling traffic with respect to data traffic. Performance of both distributed and centralized CoMP-CS are compared in terms of convergence delay and traffic overhead. Finally, we analyze the impact of the periodicity of CS operations on mobile performance, in terms of average UEs throughput, in the presence of different cell loads

A cloud-enabled small cell architecture in 5G networks for broadcast/multicast services

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The evolution of 5G suggests that communication networks become sufficiently flexible to handle a wide variety of network services from various domains. The virtualization of small cells as envisaged by 5G, allows enhanced mobile edge computing capabilities, thus enabling network service deployment and management near the end user. This paper presents a cloud-enabled small cell architecture for 5G networks developed within the 5G-ESSENCE project. This paper also presents the conformity of the proposed architecture to the evolving 5G radio resource management architecture. Furthermore, it examines the inclusion of an edge enabler to support a variety of virtual network functions in 5G networks. Next, the improvement of specific key performance indicators in a public safety use case is evaluated. Finally, the performance of a 5G enabled evolved multimedia broadcast multicast services service is evaluated.Peer ReviewedPostprint (author's final draft

Definition and specification of connectivity and QoE/QoS management mechanisms – final report

This document summarizes the WP5 work throughout the project, describing its functional architecture and the solutions that implement the WP5 concepts on network control and orchestration. For this purpose, we defined 3 innovative controllers that embody the network slicing and multi tenancy: SDM-C, SDM-X and SDM-O. The functionalities of each block are detailed with the interfaces connecting them and validated through exemplary network processes, highlighting thus 5G NORMA innovations. All the proposed modules are designed to implement the functionality needed to provide the challenging KPIs required by future 5G networks while keeping the largest possible compatibility with the state of the art

View on 5G Architecture: Version 2.0

The 5G Architecture Working Group as part of the 5GPPP Initiative is looking at capturing novel trends and key technological enablers for the realization of the 5G architecture. It also targets at presenting in a harmonized way the architectural concepts developed in various projects and initiatives (not limited to 5GPPP projects only) so as to provide a consolidated view on the technical directions for the architecture design in the 5G era. The first version of the white paper was released in July 2016, which captured novel trends and key technological enablers for the realization of the 5G architecture vision along with harmonized architectural concepts from 5GPPP Phase 1 projects and initiatives. Capitalizing on the architectural vision and framework set by the first version of the white paper, this Version 2.0 of the white paper presents the latest findings and analyses with a particular focus on the concept evaluations, and accordingly it presents the consolidated overall architecture design

View on 5G Architecture: Version 1.0

The current white paper focuses on the produced results after one year research mainly from 16 projects working on the abovementioned domains. During several months, representatives from these projects have worked together to identify the key findings of their projects and capture the commonalities and also the different approaches and trends. Also they have worked to determine the challenges that remain to be overcome so as to meet the 5G requirements. The goal of 5G Architecture Working Group is to use the results captured in this white paper to assist the participating projects achieve a common reference framework. The work of this working group will continue during the following year so as to capture the latest results to be produced by the projects and further elaborate this reference framework. The 5G networks will be built around people and things and will natively meet the requirements of three groups of use cases: • Massive broadband (xMBB) that delivers gigabytes of bandwidth on demand • Massive machine-type communication (mMTC) that connects billions of sensors and machines • Critical machine-type communication (uMTC) that allows immediate feedback with high reliability and enables for example remote control over robots and autonomous driving. The demand for mobile broadband will continue to increase in the next years, largely driven by the need to deliver ultra-high definition video. However, 5G networks will also be the platform enabling growth in many industries, ranging from the IT industry to the automotive, manufacturing industries entertainment, etc. 5G will enable new applications like for example autonomous driving, remote control of robots and tactile applications, but these also bring a lot of challenges to the network. Some of these are related to provide low latency in the order of few milliseconds and high reliability compared to fixed lines. But the biggest challenge for 5G networks will be that the services to cater for a diverse set of services and their requirements. To achieve this, the goal for 5G networks will be to improve the flexibility in the architecture. The white paper is organized as follows. In section 2 we discuss the key business and technical requirements that drive the evolution of 4G networks into the 5G. In section 3 we provide the key points of the overall 5G architecture where as in section 4 we elaborate on the functional architecture. Different issues related to the physical deployment in the access, metro and core networks of the 5G network are discussed in section 5 while in section 6 we present software network enablers that are expected to play a significant role in the future networks. Section 7 presents potential impacts on standardization and section 8 concludes the white paper

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

FlexDRAN: Flexible centralization in disaggregated radio access networks

Radio Access Network (RAN) disaggregation allows operators to mix-and-match multivendor components and bring RAN services from one end to the other. Despite this goal, issues of resource misuse or performance undershoot may arise because of inflexible RAN function deployment and uncoordinated decision-making across different network segments. To address these issues, this paper considers full flexibility in the synthesis of end-to-end RAN services from a set of disaggregated and uncoordinated components. In particular, five design factors are jointly considered to maximize the overall network spectral efficiency: (1) User association, (2) Remote radio unit clustering, (3) RAN functional split, (4) Fronthaul network routing, and (5) Baseband unit placement. To efficiently deal with the formulated problem, we propose a two-level turbo-based solution and compare its performance with several related works. The simulation results show that our proposed solution can not only achieve a 1.33-times spectral efficiency gain compared with state-of-the-art methods, but also provides 1.27 and 1.74 multiplexing benefits for computing and networking resources, respectively.This work is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement 5Growth (No. 856709), Affordable5G (No. 957317), DAEMON (No. 101017109), and 6GBrain (No. 101017226)

Enhancing RAN throughput by optimized CoMP controller placement in optical metro networks

The fifth generation (5G) of mobile communications will target unprecedented network performance and quality of service for end users. Among the various aspects which will be addressed in 5G, advanced cell coordination is deemed as crucial to maximize network throughput. In particular, in this paper, we refer to coordinated multipoint (CoMP) techniques that allow coordinating groups of cells (i.e., clusters) through a coordination controller, namely, a radio controller coordinator (RCC), to enhance the mobile network throughput by reducing interference. We focus on the placement of RCCs in the metro optical network and on its impact on the performance of cell coordination. We provide strategies to perform an optimized placement of such controllers in metro optical networks in order to maximize network throughput via cell coordination. Several CoMP techniques have been designed, whose throughput gain is affected by various factors, e.g., gain increases with the cluster size, while it decreases for larger latencies between the RCC and cells. As current metro networks are characterized by a hierarchical architecture with different levels of central offices, the choice of where to place controllers to maximize throughput gain can be optimized according to several factors, i.e., network geographical dimension, cells density, and available technology. In addition, selection of the most appropriate CoMP technique to be used in each cluster is not trivial, as the gain provided by the various techniques is differently affected by cluster size and latency between the RCC and cells. Our results show that under certain conditions optimized placement provides up to around 10% higher coordination gain with respect to fixed controller placement. Moreover, when adopting fronthaul technology, the coordination gain provided by an optimized controller placement may increase up to 20% in comparison to fixed placement