Flexible Functional Split in C-RAN with Renewable Energy Powered Remote Radio Units

Wang, Liumeng; Zhou, Sheng

doi:10.1109/iccw.2018.8403571

Cited by 11 publications

(4 citation statements)

References 13 publications

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“…Some works have also put emphasis on the impact that this type of architectures might have over energy consumption. In this sense, split selection is optimized considering energy constraints in [23], [24], while the authors of [25] propose an energy-aware split selection algorithm for scenarios with Unmanned Aerial Vehicles (UAVs). In the same line, the selection of functional splits in [26], as well as their duration, considers energy constraints over a network with energy harvesting-enabled radio elements.…”

Section: Related Workmentioning

confidence: 99%

Understanding the Performance of Flexible Functional Split in 5G vRAN Controllers: A Markov Chain-Based Model

Díez

Hervella

Agüero

2021

IEEE Trans. Netw. Serv. Manage.

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We study Flexible Functional Split functionality of 5G vRAN controllers in 5G networks. We propose an innovative model, based on a Markov Chain, which can be used to characterize their performance. We consider both infinite and finite-buffer controllers. In the former, frames would not be lost (provided the system works in a stable regime), and we thus focus on the time frames stay at the controller. For the finite-buffer controller, there might be losses, and we analyze the trade-off between time at the controller (which might hinder the stringent delay requirements of 5G services), and loss probability. Matrix-geometric techniques are used to resolve the corresponding Quasi-Birth-Death process. The validity of the proposed model is assessed by means of an extensive experiment campaign carried out over an ad-hoc eventdriven simulator, which is also used to broaden the analysis, considering different service rate distributions, as well as the variability of the studied performance indicators. The results show that the proposed model can be effectively exploited to tackle the dimensioning of these systems, as it sheds light on how their configuration impacts the expected delay and loss rate.

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Section: Related Workmentioning

confidence: 99%

Understanding the Performance of Flexible Functional Split in 5G vRAN Controllers: A Markov Chain-Based Model

Díez

Hervella

Agüero

2021

IEEE Trans. Netw. Serv. Manage.

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“…The authors detail the energy consumption in virtual small cells (vSCs) and implement reinforcement learning (RL) methods to optimize the FS decisions between the vSCs and a macro base station [6], [7]. Meanwhile, Wang et al propose a heuristic solution for an architecture that the functions that are split between the RRHs and BBUs [8]. In addition, Ko et al focus on a similar architecture and formulate a constrained Markov decision process model [9].…”

Section: Related Workmentioning

confidence: 99%

Reinforcement Learning Based Dynamic Function Splitting in Disaggregated Green Open RANs

Pamuklu,

Erol-Kantarci,

Ersoy

2020

Preprint

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With the growing momentum around Open RAN (O-RAN) initiatives, performing dynamic Function Splitting (FS) in disaggregated and virtualized Radio Access Networks (vRANs), in an efficient way, is becoming highly important. An equally important efficiency demand is emerging from the energy consumption dimension of the RAN hardware and software. Supplying the RAN with Renewable Energy Sources (RESs) promises to boost the energy-efficiency. Yet, FS in such a dynamic setting, calls for intelligent mechanisms that can adapt to the varying conditions of the RES supply and the traffic load on the mobile network. In this paper, we propose a reinforcement learning (RL)based dynamic function splitting (RLDFS) technique that decides on the function splits in an O-RAN to make the best use of RES supply and minimize operator costs. We also formulate an operational expenditure minimization problem. We evaluate the performance of the proposed approach on a real data set of solar irradiation and traffic rate variations. Our results show that the proposed RLDFS method makes effective use of RES and reduces the cost of an MNO. We also investigate the impact of the size of solar panels and batteries which may guide MNOs to decide on proper RES and battery sizing for their networks.

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“…Then, in their next study, they enhance this study and provide a solution for an online problem that dynamically change the splitting decisions according to the traffic load and the harvested energy [29]. Meanwhile, Wang et al propose a novel model to maximize the throughput of the network by solving the function splitting problem with RESs [30]. On the contrary, Ko et al choose the throughput as a constraint in their problem [31].…”

Section: Using Renewable Energy Sources In a C-ran Architecturementioning

confidence: 99%

GROVE: A Cost-Efficient Green Radio over Ethernet Architecture for Next Generation Radio Access Network

Pamuklu,

Ersoy

2020

Preprint

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Centralized/Cloud Radio Access Network (C-RAN) comes into prominence to reduce the rising energy consumptions and maintenance difficulties of next-generation networks. However, C-RAN has strict delay requirements, and it needs large fronthaul bandwidth. Function splitting and Radio over Ethernet are two promising approaches to reduce these drawbacks of the C-RAN architecture. Meanwhile, the usage of renewable energy sources in a C-RAN boosts the energy-efficiency potential of this network. In this paper, we propose a novel model, which is called Green Radio OVer Ethernet (GROVE), that merges these three approaches to maximize the benefits of C-RAN while maintaining the economic feasibility of this architecture. We briefly explain this model and formulate an operational expenditure minimization problem by considering the several restrictions due to the network design and the service provisioning. Then we linearize this problem to solve it with a mixed-integer linear programming solver. Our experimental results show that our solution surpasses classical disjoint approaches for any diversity in a city population and the geographical location of this city. Besides, our feasibility study guides the mobile network operators to choose the proper size of solar panels and the batteries in this next-generation network.

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Flexible Functional Split in C-RAN with Renewable Energy Powered Remote Radio Units

Cited by 11 publications

References 13 publications

Understanding the Performance of Flexible Functional Split in 5G vRAN Controllers: A Markov Chain-Based Model

Understanding the Performance of Flexible Functional Split in 5G vRAN Controllers: A Markov Chain-Based Model

Reinforcement Learning Based Dynamic Function Splitting in Disaggregated Green Open RANs

GROVE: A Cost-Efficient Green Radio over Ethernet Architecture for Next Generation Radio Access Network

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