A novel cloud RAN architecture for 5G HetNets and QoS evaluation

Chabbouh, Olfa; Rejeb, Sonia Ben; Choukair, Zièd; Agoulmine, Nazim

doi:10.1109/isncc.2016.7746121

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…When it is impossible to use the maximum MCS for some users, it could be possible to use a lower MCS index making a place for one or more additional users. As can be seen in constraint (3), this extra degree of liberty compared to the non-coordination schemes (where a single MCS may be assigned) can only be beneficial, producing higher throughput and number of served users or at least as good as the no-coordination.…”

Section: A Average Throughput Per Usermentioning

confidence: 99%

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On Coordinated Scheduling of Radio and Computing Resources in Cloud-RAN

Sharara

Hoteit

Brown³

2023

IEEE Trans. Netw. Serv. Manage.

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Cloud Radio Access Network is a promising mobile network architecture based on centralizing the baseband processing of many cellular base stations in a BBU (BaseBand Unit) pool. Such architecture has many advantages. However, computing resources are shared among the base stations connected to the BBU pool. It is challenging to schedule the processing of users' data, especially on overloaded BBU pools, while respecting the time constraints imposed by the Hybrid Automatic Repeat Request (HARQ) mechanism. Given that the processing time of users' data and the computing requirement depends on the radio parameters such as the Modulation and Coding Scheme (MCS), we propose to enable the coordination between radio and computing resources schedulers; such coordination makes the selection of MCS dependent on the availability of radio and computing resources and on the ability to process data while respecting the HARQ-deadline. In this context, we propose and evaluate three Integer Linear Programming (ILP)-based schemes and three low-complexity heuristics, demonstrating their ability to reduce the wasted transmission power. Moreover, we evaluate the performance of the coordination under a multiservices scenario consisting of two services having heterogeneous requirements, enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC).

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Section: A Average Throughput Per Usermentioning

confidence: 99%

“…On the other hand, computing resources of the Fig. 1: Cloud-RAN architecture [3] Fig. 2: Scheduling the processing of users in the BBU pool.…”

Section: Introductionmentioning

confidence: 99%

On Coordinated Scheduling of Radio and Computing Resources in Cloud-RAN

Sharara

Hoteit

Brown³

2023

IEEE Trans. Netw. Serv. Manage.

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“…One of the main benefits is the capacity for spectrum efficiency since the framework for processing base stations is centralized in a physical BBU located in telecommunications centers; this makes it easy to share the signal, traffic data and information in the state channels of the users that are actively using the system [9].…”

Section: B Hybrid Fiber Radio Systemsmentioning

confidence: 99%

A Fuzzy Strategy for Planning Centralized Access Networks in the Installation of Hybrid Fiber Radio Systems

Costa

Silva

et al. 2020

IEEE Access

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5G networks have arrived and are able to shift paradigms within the areas of connectivity, maintainability, scalability and availability. Their aim is to ensure that users can remain online with their devices at any time and in any place. In light of this, solutions for centralized networks are becoming attractive since they are manageable and low-cost. In these conditions, the use of computing techniques such as fuzzy logic benefits the supervision and planning of networks by optimizing and controlling resources as well as managing the system. However, planning a centralized network tends to raise challenges in the optical sectors that are located between the telecommunications center and the base station. Technologies such as radio over fiber are being examined to meet the demands in the fronthaul market, although they raise many other challenges. For this reason, in this study, we have adopted an intelligent strategy to determine in a balanced way which radio over fiber signals should be allocated in the optical sector. This strategy is implemented using fuzzy logic and may be used in decision making to plan the future of centralized networks. The results show that it is possible to make tradeoffs between the capital expenditure and performance of the system.

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“…Cloud RAN holds the potential in giving effective communication and information exchange among the terminals. When C‐RAN is modeled with the assistance of SDN, it gives a space to configure and manage the dense small cells deployment . To enhance the QoS in C‐RAN, BBU pool is relocated into BBU and Remote Radio Head (RRH) where BBU is enabled with the central processing unit to provide network coordination and management.…”

Section: Related Workmentioning

confidence: 99%

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

Bashir

Arul

Basheer

et al. 2019

Trans Emerging Tel Tech

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The networks are evolving drastically since last few years in order to meet user requirements. For example, the 5G is offering most of the available spectrum under one umbrella. In this work, we will address the resource allocation problem in fifth-generation (5G) networks, to be exact in the Cloud Radio Access Networks (C-RANs). The radio access network mechanisms involve multiple network topologies that are isolated based on the spectrum bands and it should be enhanced with numerous access technology in the deployment of 5G network. The C-RAN is one of the optimal technique to combine all the available spectral bands. However, existing C-RAN mechanisms lacks the intelligence perspective on choosing the spectral bands. Thus, C-RAN mechanism requires an advanced tool to identify network topology to allocate the network resources for substantial traffic volumes. Therefore, there is a need to propose a framework that handles spectral resources based on user requirements and network behavior. In this work, we introduced a new C-RAN architecture modified as multitier Heterogeneous Cloud Radio Access Networks in a 5G environment. This architecture handles spectral resources efficiently. Based on the simulation analysis, the proposed multitier H-CRAN architecture with improved control unit in network management perspective enables augmented granularity, end-to-end optimization, and guaranteed quality of service by 15 percentages over the existing system.Trans Emerging Tel Tech. 2019;30:e3627.wileyonlinelibrary.com/journal/ett spectrum like WiFi. 2 The advanced antennas with multiple input and multiple output technologies can be adopted in the evolving 5G to provide higher data rate. 3,4 The colossal requirements of future 5G networks cannot be accomplished by the existing radio access networks (RANs), wherein the base band units (BBUs) and radio units are consolidated. 2 Meanwhile, the cloud-enabled services in 5G ecosystem cater heterogeneous communication framework utilizing advanced virtualization techniques. The network virtualization stimulates multiservice and multitenancy for efficient network operations and service provisions, which, in turn, offers new-fangled service-oriented and edge-cloud 5G architectures with enhanced Quality of Experience (QoE). 5 Thus, the current RAN architectures need to be further extended with various virtualization techniques to develop Cloud RAN (C-RAN). Cloud RANs abutments the correlation of Access Points (APs) to the pool of BBU via a troop of transport links in the Control Unit (CU), 6 which conquers the limitations in the traditional RAN. 7 However, C-RAN requires an intelligent technique to recognize the topology of the network in the mobility stage and to locate the resources, as the vast traffic volume created by the sampled radio signals are directly transported to the CU. 8 The next-generation networks are expected to learn consistently based on the varied user behavior and spectral stability that depends on both the user's environment and network behavior. 9 Thereby, sea...

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A novel cloud RAN architecture for 5G HetNets and QoS evaluation

Cited by 7 publications

References 5 publications

On Coordinated Scheduling of Radio and Computing Resources in Cloud-RAN

On Coordinated Scheduling of Radio and Computing Resources in Cloud-RAN

A Fuzzy Strategy for Planning Centralized Access Networks in the Installation of Hybrid Fiber Radio Systems

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

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