On Performance Analysis of Single Frequency Network with C-RAN

Centralized-RAN (C-RAN) is an architectural trend that uses resource sharing and a set of interference mitigation techniques to reduce capital and operational expenditures for mobile network operators (MNOs). One of the technical enablers of a C-RAN solution is single frequency network (SFN) that curbs the interference and allows MNOs to transmit over single frequency across coordinated cells. One of the main advantages of SFN is that it reduces the number of handovers between neighboring cells while improving the overall system performance. In contrast to previous approaches that demonstrate some of the most prominent C-RAN features, in this paper, we first investigate two different SFN deployment scenarios’ characteristics, benefits, and limitations. Second, we perform a simulation analysis of non-SFN and SFN without joint scheduling to observe signal to interference ratio heatmap distribution of the experimental test-site using similar system configurations. Finally, we perform an experimental analysis of joint scheduling in SFN based on coordinated inter baseband units scenario using C-RAN in a realistic environment. The experimental results are tested on a real operating site of a major MNO’s infrastructure in Turkey. Through experimental results, we show overall performance gains of SFN feature in terms of different key performance indicators that are obtained from coordinating remote radio units in an SFN cell. Finally, we discuss about the main takeaways, lessons learned, and challenges of the considered SFN implementation

Intelligent service orchestration in edge cloud networks

The surge in data traffic is challenging for network infrastructure owners coping with stringent service requirements (e.g., high bandwidth, ultralow latency) as well as shrinking per-gigabyte revenues. Network softwarization and edge computing are powerful candidates to mitigate these issues. In parallel, there is an increasing demand for network virtualization and container-based services. In this study, we investigate the management of software defined networking (SDN)-based transport network and edge cloud service orchestration. To this end, we use a machine learning (ML)-based design to manage both transport and edge cloud resources of a mobile network effectively. To generate and use real-world data inside our ML platform, we use the Graphical Network Simulator-3 (GNS3) emulator environment. Our emulation results indicate that almost all of the trained ML models can accurately select the correct edge clouds (ECs) (i.e., with high test accuracy) under the considered two scenarios when transport and EC network parameters are considered in comparison to models trained via only transport or cloud-based parameters. At the end of the article, we also provide an evolved architecture where the proposed ML platform can be embedded in an end-to-end mobile network architecture and H2020 5Growth project's baseline management platform.This work has been partially funded by the EU H2020 5Growth Project (grant no. 856709), by MINECO grant TEC2017-88373-R (5G-REFINE), and Generalitat de Catalunya grant 2017 SGR, 1195

Service based virtual RAN architecture for next generation cellular systems

Service based architecture (SBA) is a paradigm shift from Service-Oriented Architecture (SOA) to microservices, combining their principles. Network virtualization enables the application of SBA in cellular systems. To better guide the software design of this virtualized cellular system with SBA, this paper presents a software perspective and a positional approach to using fundamental development principles for adapting SBA in virtualized Radio Access Networks (vRANs). First, we present the motivation for using an SBA in cellular radio systems. Then, we explore the critical requirements, key principles, and components for the software to provide radio services in SBA. We also explore the potential of applying SBA-based Radio Access Network (RAN) by comparing the functional split requirements of 5G RAN with existing open-source software and accelerated hardware implementations of service bus, and discuss the limitations of SBA. Finally, we present some discussions, future directions, and a roadmap of applying such a high-level design perspective of SBA to next-generation RAN infrastructure.This work was supported in part by the European Union (EU) H2020 5GROWTH Project under Grant 856709, in part by the Generalitat de Catalunya under Grant 2017 SGR 1195, and in part by the National Program on Equipment and Scientific and Technical Infrastructure under the European Regional Development Fund (FEDER) under Grant EQC2018-005257-P