Identifying 5G system enhancements: enabling technologies for multi-service networks

Proceeding of: 2018 IEEE Conference on Standards for Communications and Networking (CSCN)The fifth generation (5G) of mobile and wireless communications networks aims at addressing a diverse set of use cases, services, and applications with a particular focus on enabling new business cases via network slicing. The development of 5G has thus advanced quickly with research projects and standardization efforts resulting in the 5G baseline architecture. Nevertheless, for the realization of native end-to-end (E2E) network slicing, further features and optimizations shall still be introduced. In this paper, we provide a gap analysis of current 5G system (5GS) with respect to some specific enhancements and detail our insights on the enabling innovations that can fill the identified gaps. We will then discuss the essential building blocks and design principles of an evolved 5G baseline architecture capitalizing on the innovations that are being developed.This work has been performed in the framework of the H2020 project 5G-MoNArch co-funded by the EU

A flexible network architecture for 5G systems

In this paper, we define a flexible, adaptable, and programmable architecture for 5G mobile networks, taking into consideration the requirements, KPIs, and the current gaps in the literature, based on three design fundamentals: (i) split of user and control plane, (ii) service-based architecture within the core network (in line with recent industry and standard consensus), and (iii) fully flexible support of E2E slicing via per-domain and cross-domain optimisation, devising inter-slice control and management functions, and refining the behavioural models via experiment-driven optimisation. The proposed architecture model further facilitates the realisation of slices providing specific functionality, such as network resilience, security functions, and network elasticity. The proposed architecture consists of four different layers identified as network layer, controller layer, management and orchestration layer, and service layer. A key contribution of this paper is the definition of the role of each layer, the relationship between layers, and the identification of the required internal modules within each of the layers. In particular, the proposed architecture extends the reference architectures proposed in the Standards Developing Organisations like 3GPP and ETSI, by building on these while addressing several gaps identified within the corresponding baseline models. We additionally present findings, the design guidelines, and evaluation studies on a selected set of key concepts identified to enable flexible cloudification of the protocol stack, adaptive network slicing, and inter-slice control and management.This work has been performed in the framework of the H2020 project 5G-MoNArch co-funded by the E

End-to-End Data Analytics Framework for 5G Architecture

Data analytics can be seen as a powerful tool for the fifth-generation (5G) communication system to enable the transformation of the envisioned challenging 5G features into a reality. In the current 5G architecture, some first features toward this direction have been adopted by introducing new functions in core and management domains that can either run analytics on collected communication-related data or can enhance the already supported network functions with statistics collection and prediction capabilities. However, possible further enhancements on 5G architecture may be required, which strongly depend on the requirements as set by vertical customers and the network capabilities as offered by the operator. In addition, the architecture needs to be flexible in order to deal with network changes and service adaptations as requested by verticals. This paper explicitly describes the requirements for deploying data analytics in a 5G system and subsequently presents the current status of standardization activities. The main contribution of this paper is the investigation and design of an integrated data analytics framework as a key enabling technology for the service-based architectures (SBAs). This framework introduces new functional entities for application-level, data network, and access-related analytics to be integrated into the already existing analytics functionalities and examines their interactions in a service-oriented manner. Finally, to demonstrate predictive radio resource management, we showcase a particular implementation for application and radio access network analytics, based on a novel database for collecting and analyzing radio measurements

5G infrastructures supporting end-user and operational services:The 5G-XHaul architectural perspective

We propose an optical-wireless 5G infrastructure offering converged fronthauling/backhauling functions to support both operational and end-user cloud services. A layered architectural structure required to efficiently support these services is shown. The data plane performance of the proposed infrastructure is evaluated in terms of energy consumption and service delay through a novel modelling framework. Our modelling results show that the proposed architecture can offer significant energy savings but there is a clear trade-off between overall energy consumption and service delay.Peer ReviewedPostprint (author's final draft

Wireless-optical network convergence: enabling the 5G architecture to support operational and end-user services

© 2017 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.This article presents a converged 5G network infrastructure and an overarching architecture to jointly support operational network and end-user services, proposed by the EU 5G PPP project 5G-XHaul. The 5G-XHaul infrastructure adopts a common fronthaul/backhaul network solution, deploying a wealth of wireless technologies and a hybrid active/passive optical transport, supporting flexible fronthaul split options. This infrastructure is evaluated through a novel modeling. Numerical results indicate significant energy savings at the expense of increased end-user service delay.Peer ReviewedPostprint (author's final draft

Inter-Cell Interference-Aware Radio Resource Management for Femtocell Networks.

The widespread data demand in emerging wireless cellular technologies necessitates the evolution of traditional networks’ deployment to accommodate the ever increasing coverage and capacity requirements. In emerging wireless systems a hierarchical multi-level network that consists of a mixture of outdoor small cells (relays) and indoor small cells (femtocell) deployments underneath the traditional macro-cell architecture can be seen as a key deployment strategy to meet these growing capacity demands. In such networks, Femtocell technology has attracted much attention as a key “player” to address coverage and capacity issues mainly in home and enterprise environments. However, a major challenge that arises in such indoor networks originates from the inter-cell interference between the femtocells (commonly known as co-tier interference), assuming that femtocells share the same spectrum. The main objectives of this thesis are to investigate inter-cell interference in femtocell networks and to propose efficient multi-cell scheduling mechanisms that can mitigate inter-cell interference in dense femtocell environments while maintaining spectral efficiency at acceptable level across the cells. We begin with investigating the impact of co-tier interference in femtocells, highlighting the necessity of interference mitigation mechanisms for arbitrary deployment of femtocells. In this direction, a novel low-complexity graph-coloring based interference coordination mechanism is proposed to be applied on top of intra-cell radio resource management. We additionally propose two locally centralized multi-cell scheduling frameworks that enclose adaptive graph-partitioning and weighted capacity maximization concepts. In particular, we decompose the problem in the latter case based on the Exact Generalized Travelling Salesman Problem as a close match in graph-based solutions. Extensive evaluation is provided by simulations showing a significant improvement over the state-of-the-art multi-cell scheduling benchmarks in terms of outage probability as well as user and cell throughput and thus the proposed algorithms are promising candidates of multi-cell scheduling in next generation small cell networks

Inter-cell interference-aware radio resource management for femtocell networks

The widespread data demand in emerging wireless cellular technologies necessitates the evolution of traditional networks' deployment to accommodate the ever increasing coverage and capacity requirements. In emerging wireless systems a hierarchical multi-level network that consists of a mixture of outdoor small cells (relays) and indoor small cells (femtocell) deployments underneath the traditional macro-cell architecture can be seen as a key deployment strategy to meet these growing capacity demands. In such networks, Femtocell technology has attracted much attention as a key "player" to address coverage and capacity issues mainly in home and enterprise environments. However, a major challenge that arises in such indoor networks originates from the inter-cell interference between the femtocells (commonly known as co-tier interference), assuming that femtocells share the same spectrum. The main objectives of this thesis are to investigate inter-cell interference in femtocell networks and to propose efficient multi-cell scheduling mechanisms that can mitigate inter-cell interference in dense femtocell environments while maintaining spectral efficiency at acceptable level across the cells. We begin with investigating the impact of co-tier interference in femtocells, highlighting the necessity of interference mitigation mechanisms for arbitrary deployment of femtocells. In this direction. a novel low-complex.ity graph-coloring based interference coordination mechanism is proposed to be applied on top of intra-cell radio resource management. We additionally propose two locally centralized multi-cell scheduling frameworks that enclose adaptive graph-panitioning and weighted capacity maximization concepts. In particular, we decompose the problem in the latter case based on the Exact Generalized Travelling Salesman Problem as a close match in graph-based solutions. Extensive evaluation is provided by simulations showing a significant improvement over the state-of-the-art multi-cell scheduling benchmarks in terms of outage probability as well as user and cell throughput and thus the proposed algorithms are promising candidates of multi-cell scheduling in next generation small cell networks.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Dynamic clustering framework for multi-cell scheduling in dense small cell networks

This letter proposes a novel graph-based multi-cell scheduling framework to efficiently mitigate downlink inter-cell interference in small cell OFDMA networks. This framework incorporates dynamic clustering combined with channel-aware resource allocation to provide tunable quality of service measures at different levels. Our extensive evaluation study shows that a significant improvement in user's spectral efficiency is achievable, while also maintaining relatively high cell spectral efficiency via empirical tuning of re-use factor across the cells according to the required QoS constraints