Abstract
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.
Highlights
The cloud radio access network (C-RAN) architecture aims at warranting quality of service (QoS) to all users based on the following three components: (a) the remote radio head (RRH), which includes the antenna together with the radio frequency components and has the duty for the signal’s transmission/reception, (b) the baseband units (BBUs), which form a BBU pool and are responsible for the baseband signal processing, and (c) a high-capacity fronthaul network, which connects the BBU pool with the remote radio heads (RRHs) via the common public radio interface (CPRI) [4–7]
In [24,25], the case of overlapping cells has been included in the model of [23], while in [26] a generalization of [23] is considered based on the fact that the RRHs may form more than one clusters according to their resource units (RRUs)
Two new loss models that consider multirate traffic are proposed in this paper, namely the compound Poisson multi-class single-cluster (c-MC-SC) and the compound Poisson multi-class multi-cluster (c-MC-MC) models, in order to analyze a C-RAN that accommodates different service-classes whose calls arrive in the system via a compound Poisson process (PP)
Summary
Based on the quite recent report of [1], it is estimated to have 4.4 billion fifth-generation (5G) subscriptions and a total global mobile data traffic of 288 EB/month by the end of 2027. In [24,25], the case of overlapping cells has been included in the model of [23], while in [26] a generalization of [23] is considered based on the fact that the RRHs may form more than one clusters according to their RRU capacity. In [46], we extended both models by assuming that a finite number of MUs has the responsibility to generate traffic towards the RRHs. Recently, a new multirate loss model was proposed in [47] with the aim to recursively compute CBP in a C-RAN that serves Poisson traffic, via the classical. We extend the MC-SC and MC-MC models to include the significant (in terms of network dimensioning) scenario of having RRHs that are responsible for serving compound Poisson traffic.
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