45,483 research outputs found
Iris: Deep Reinforcement Learning Driven Shared Spectrum Access Architecture for Indoor Neutral-Host Small Cells
We consider indoor mobile access, a vital use case for current and future
mobile networks. For this key use case, we outline a vision that combines a
neutral-host based shared small-cell infrastructure with a common pool of
spectrum for dynamic sharing as a way forward to proliferate indoor small-cell
deployments and open up the mobile operator ecosystem. Towards this vision, we
focus on the challenges pertaining to managing access to shared spectrum (e.g.,
3.5GHz US CBRS spectrum). We propose Iris, a practical shared spectrum access
architecture for indoor neutral-host small-cells. At the core of Iris is a deep
reinforcement learning based dynamic pricing mechanism that efficiently
mediates access to shared spectrum for diverse operators in a way that provides
incentives for operators and the neutral-host alike. We then present the Iris
system architecture that embeds this dynamic pricing mechanism alongside
cloud-RAN and RAN slicing design principles in a practical neutral-host design
tailored for the indoor small-cell environment. Using a prototype
implementation of the Iris system, we present extensive experimental evaluation
results that not only offer insight into the Iris dynamic pricing process and
its superiority over alternative approaches but also demonstrate its deployment
feasibility
Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges
As a promising paradigm for fifth generation (5G) wireless communication
systems, cloud radio access networks (C-RANs) have been shown to reduce both
capital and operating expenditures, as well as to provide high spectral
efficiency (SE) and energy efficiency (EE). The fronthaul in such networks,
defined as the transmission link between a baseband unit (BBU) and a remote
radio head (RRH), requires high capacity, but is often constrained. This
article comprehensively surveys recent advances in fronthaul-constrained
C-RANs, including system architectures and key techniques. In particular, key
techniques for alleviating the impact of constrained fronthaul on SE/EE and
quality of service for users, including compression and quantization,
large-scale coordinated processing and clustering, and resource allocation
optimization, are discussed. Open issues in terms of software-defined
networking, network function virtualization, and partial centralization are
also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin
note: text overlap with arXiv:1407.3855 by other author
Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells
Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.Peer ReviewedPostprint (author's final draft
Creating Tailored and Adaptive Network Services with the Open Orchestration C-RAN Framework
Next generation wireless communications networks will leverage
software-defined radio and networking technologies, combined with cloud and fog
computing. A pool of resources can then be dynamically allocated to create
personalized network services (NSs). The enabling technologies are abstraction,
virtualization and consolidation of resources, automatization of processes, and
programmatic provisioning and orchestration. ETSI's network functions
virtualization (NFV) management and orchestration (MANO) framework provides the
architecture and specifications of the management layers. We introduce OOCRAN,
an open-source software framework and testbed that extends existing NFV
management solutions by incorporating the radio communications layers. This
paper presents OOCRAN and illustrates how it monitors and manages the pool of
resources for creating tailored NSs. OOCRAN can automate NS reconfiguration,
but also facilitates user control. We demonstrate the dynamic deployment of
cellular NSs and discuss the challenges of dynamically creating and managing
tailored NSs on shared infrastructure.Comment: IEEE 5G World Forum 201
Soft-Defined Heterogeneous Vehicular Network: Architecture and Challenges
Heterogeneous Vehicular NETworks (HetVNETs) can meet various
quality-of-service (QoS) requirements for intelligent transport system (ITS)
services by integrating different access networks coherently. However, the
current network architecture for HetVNET cannot efficiently deal with the
increasing demands of rapidly changing network landscape. Thanks to the
centralization and flexibility of the cloud radio access network (Cloud-RAN),
soft-defined networking (SDN) can conveniently be applied to support the
dynamic nature of future HetVNET functions and various applications while
reducing the operating costs. In this paper, we first propose the multi-layer
Cloud RAN architecture for implementing the new network, where the multi-domain
resources can be exploited as needed for vehicle users. Then, the high-level
design of soft-defined HetVNET is presented in detail. Finally, we briefly
discuss key challenges and solutions for this new network, corroborating its
feasibility in the emerging fifth-generation (5G) era
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