A framework for resources allocation in virtualised C-RAN

Abstract

General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Abstract-The vast growth in mobile data traffic with its increasing capacity demands necessitates investigating future solutions to cope with these challenges. Network Virtualisation is considered one potential solution to simplify the current wireless networks. Recently efforts have been made to show the performance gains of different resource allocation schemes in legacy LTE air interface virtualization. Moreover Cloud -based mobile networks are anticipated to play a significant role for next generation mobile networks. This paper investigates the potential deployment benefits of a novel resource virtualization algorithm (Traffic Aware Joint Scheduling) in Cloud-RANs (C-RAN). Air interface resources are coordinated and allocated dynamically by a hypervisor among different virtual operators (VOs). Three distinctive schemes are proposed and evaluated against standard Round Robin (RR) C-RAN scheduling. Simulation results show improvements in the throughput of the mobile video traffic and reduction in end-to-end delay for delay sensitive applications. In addition, an assessment of fairness guarantee is considered across all users. Note that this paper considers the impact of the proposed schemes on the transmission/data plane.

RAN Virtualization: How Hard Is It to Fully Achieve?

“…Moreover, the integration of new technologies such as beamforming, multi-user MIMO, massive MIMO, NOMA, and mmWave communications, along with clustering in the C-RAN architecture, has been explored in [65], [66], [67], [68]. Further contributions (e.g., [69][70][71][72][73][74][75][76][77][78][79][80][81][82][83]) have focused on developing new topology reconfigurations, resource allocation algorithms, and transmission strategies to enhance C-RAN throughput. As fronthaul delay remains a significant drawback of C-RAN, research efforts have also concentrated on minimizing end-to-end delay in C-RAN.…”

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“…Further advancements in 2016 included research [34] that utilized C-RAN architecture to propose a resource provision-ing strategy aimed at lowering power consumption at cell sites and in the cloud, addressing fluctuations in per-user capacity demand. In another study [35], the focus was on addressing interference and energy efficiency issues in small cell deployments using C-RAN virtualization technologies, introducing an adaptive mechanism within a Software-Defined Wireless Network (SDWN) paradigm. The same year, research [36] delved into resource virtualization within C-RAN, ex-amining wireless interface virtualization, traffic-aware joint scheduling, and collective programming for spectral efficiency enhancement.…”

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“…The algorithm is applicable in the context of heterogeneous LTE-A network aiming to achieve slicing and on-demand delivery of radio resources. The authors in [164] investigate air interface resource virtualization, coordination, and its dynamically allocation by a hypervisor among different virtual operators in V-CRAN. Reference [165] provides a resource allocation framework for V-CRAN and furthermore explores energy consumption.…”