Split analysis and fronthaul dimensioning in 5G C-RAN to guarantee ultra low latency

Touati, Hadjer; Castel-Taleb, Hind; Jouaber, Badii; Akbarzadeh, Sara

doi:10.1109/ccnc46108.2020.9045398

Cited by 3 publications

(2 citation statements)

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“…The set Ω =T r,s includes two kinds of blocking states: those that express the CRUs unavailability and those that express both RRUs and CRUs unavailability. Equations ( 10) and (11) reveal that the determination of B TC r,r,s and B TC c,r,s is complex since it is mandatory to have enumeration/processing of Ω. Thus, we suggest using this method only for tutorial examples.…”

Section: The Brute Force Methodsmentioning

confidence: 99%

“…In the recent past, various 5G C-RAN aspects have been studied, including: (a) functional splits, dimensioning and capacity issues of the fronthaul network [8][9][10][11][12], (b) privacy and security challenges as well as detailed frameworks for potential security attacks and threats [13][14][15][16], (c) energy and cost saving issues together with energy saving operating strategies [3,[17][18][19][20] and (d) cooperation problems between different mobile network operators [21,22]. On the other hand, there exists a limited number of papers that investigate the quite interesting subject of MUs' call admission control in a 5G C-RAN and focus on proposing analytical algorithms (based on efficient and usually recursive formulas) for the computation of call blocking probabilities (CBP) [23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

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Multiservice Loss Models in C-RAN Supporting Compound Poisson Traffic

et al. 2022

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In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units (RUs) and are separated from the remote radio heads (RRHs). The RRHs are grouped into clusters based on their capacity in radio RUs. Each RRH serves different service-classes whose calls have different requirements in terms of radio and computational RUs and follow a compound Poisson process. This means that calls arrive in batches while each batch of calls follows a Poisson process. If the RUs’ requirements of an arriving call are met, then the call is accepted in the serving RRH for an exponentially distributed service time. Otherwise, call blocking occurs. We initially start our analysis with a single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time and call congestion probabilities via a convolution algorithm. Furthermore, the previous model is extended to include the more complex case of many clusters of RRHs.

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Section: The Brute Force Methodsmentioning

confidence: 99%