5 research outputs found
On the use of prioritization and network slicing features for mission critical and commercial traffic multiplexing in 5G Radio Access Networks
© 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 Public Protection and Disaster Relief (PPDR) sector is undergoing an important transition with the deployment of Mission Critical (MC) mobile broadband technology based on 3GPP standards, with multiple initiatives on-going worldwide for providing PPDR agencies with broadband communications capabilities. One common approach being adopted is the delivery of MC services together with commercial traffic over public mobile networks and the use of prioritization mechanisms to protect the MC connections in congestion situations. However, this approach leaves commercial traffic unprotected in front of a noncontrolled surge of MC traffic in specific cells since all resources would be allocated to serve this traffic. In this context, this paper proposes a solution to properly multiplex MC and commercial services with congestion protection for both types of services. The solution is based on the exploitation of the network slicing features brought into the new 5G standards. In particular, the paper describes how different slices can be parameterized in a 5G Radio Access Network (RAN) so that radio load guarantees can be established for each type of service. The proposed solution is evaluated in an illustrative scenario by means of simulations. Obtained results show the improvements in traffic isolation achievable by the slicing configuration when compared to the solution that only relies on prioritization mechanismsPeer ReviewedPostprint (author's final draft
Latency-Sensitive 5G RAN Slicing for Industry 4.0
Network slicing is a novel 5G paradigm that exploits the virtualization and softwarization of
networks to create different logical network instances over a common network infrastructure. Each instance
is tailored for specific Quality of Service (QoS) profiles so that network slicing can simultaneously support
several services with diverse requirements. Network slicing can be applied at the Core Network or at the
Radio Access Network (RAN). RAN slicing is particularly relevant to support latency-sensitive or timecritical
applications since the RAN accounts for a significant part of the end-to-end transmission latency. In
this context, this study proposes a novel latency-sensitive 5G RAN slicing solution. The proposal includes
schemes to design slices and partition (or allocate) radio resources among slices. These schemes are
designed with the objective to satisfy both the rate and latency demands of diverse applications. In
particular, this study considers applications with deterministic aperiodic, deterministic periodic and nondeterministic
traffic. The latency-sensitive 5G RAN slicing proposal is evaluated in Industry 4.0 scenarios
where stringent and/or deterministic latency requirements are common. However, it can be evolved to
support other verticals with latency-sensitive or time-critical applicationsThis work has been funded by the European Commission through the FoF-RIA Project AUTOWARE: Wireless Autonomous, Reliable and Resilient
Production Operation Architecture for Cognitive Manufacturing (No. 723909),and the Spanish Ministry of Economy, Industry, and Competitiveness, AEI,
and FEDER funds (TEC2017-88612-R)
Deep reinforcement learning based approaches for capacity sharing in radio access network slicing
Network slicing has become a fundamental capability for 5G networks to support the expected high variety of service requirements over a common physical network infrastructure. Each network slice can be customized for a specific application, making that the radio resources have to be accordingly managed by the Radio Access Network (RAN) part of the slice. In this thesis, three different Deep Reinforcement Learning (DRL) based approaches are presented to optimize the resource allocation among slices. A RAN slicing simulator scenario is developed, where the DRL mechanisms build knowledge about the network and learn how to optimize the capacity allocation for each tenant at every moment of time. The performance of each approach is studied based on simulation results, and before the comparison between the algorithms, the set of hyperparameters of each approach is tuned to optimize the learning process
On the configuration of radio resource management in a sliced RAN
Network slicing is a fundamental feature of 5G
systems that facilitates the provision of particular system
behaviours adapted to specific service/application domains on top
of a common network infrastructure. A network slice is in general
composed by a core network slice and a Radio Access Network
(RAN) slice. The realization of RAN slices is particularly
challenging because it requires configuring and operating traffic
differentiation and protection mechanisms to simultaneously
deliver multiple and diverse RAN behaviors over a given pool of
radio resources. In this context, this paper proposes to
characterize the behavior of a RAN slice through the specification
of a set of control parameters that are used to dictate the operation
of the packet scheduling function at Layer 2 and the radio
admission control function at Layer 3. An evaluation of the
suitability of these parameters for achieving efficient radio
resource sharing and isolation between RAN slices is presented
when configuring a network for supporting a slice with multiple
enhanced Mobile BroadBand services and another slice for
providing Mission Critical services. The analysis reveals the
different impact of the Layer 3 and Layer 2 parameters for
isolating services of different slices depending on whether they
require guaranteed or non-guaranteed bit rates.Peer ReviewedPostprint (published version
On the configuration of radio resource management in a sliced RAN
Network slicing is a fundamental feature of 5G
systems that facilitates the provision of particular system
behaviours adapted to specific service/application domains on top
of a common network infrastructure. A network slice is in general
composed by a core network slice and a Radio Access Network
(RAN) slice. The realization of RAN slices is particularly
challenging because it requires configuring and operating traffic
differentiation and protection mechanisms to simultaneously
deliver multiple and diverse RAN behaviors over a given pool of
radio resources. In this context, this paper proposes to
characterize the behavior of a RAN slice through the specification
of a set of control parameters that are used to dictate the operation
of the packet scheduling function at Layer 2 and the radio
admission control function at Layer 3. An evaluation of the
suitability of these parameters for achieving efficient radio
resource sharing and isolation between RAN slices is presented
when configuring a network for supporting a slice with multiple
enhanced Mobile BroadBand services and another slice for
providing Mission Critical services. The analysis reveals the
different impact of the Layer 3 and Layer 2 parameters for
isolating services of different slices depending on whether they
require guaranteed or non-guaranteed bit rates.Peer Reviewe