Multiservice Loss Models in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic

Abstract

In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units and are separated from the remote radio heads (RRHs). Based on their radio capacity, the RRHs may form one or many clusters: a single cluster when all RRHs have the same capacity and multi-clusters where RRHs of the same radio capacity are grouped in the same cluster. Each RRH services the so-called multiservice traffic, i.e., calls from many service classes with various radio and computational resource requirements. Calls arrive in the RRHs according to a quasi-random process. This means that new calls are generated by a finite number of mobile users. Arriving calls require simultaneously computational and radio resource units in order to be accepted in the system, i.e., in the serving RRH. If their requirements are met, then these calls are served in the (serving) RRH for a service time which is generally distributed. Otherwise, call blocking occurs. We start with the single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time congestion probabilities via a convolution algorithm whose accuracy is validated with the aid of simulation. Furthermore, the previous model is generalized to include the more complex case of more than one clusters.

Multiservice Loss Models in C-RAN Supporting Compound Poisson Traffic

“…More specifically, they require a single RRU (from the RRH that will serve them) and a single CRU from the BBU pool. However, in contemporary networks it is essential, for network planning, to consider a multiservice environment where MUs generate calls of various resource requirements [34][35][36][37][38][39][40][41][42][43][44][45][46]. In [45], we introduced two such multirate loss models for the C-RAN architecture and named them multi-class single-cluster and multiclass multi-cluster models (MC-SC and MC-MC, respectively).…”

“…In [45], we introduced two such multirate loss models for the C-RAN architecture and named them multi-class single-cluster and multiclass multi-cluster models (MC-SC and MC-MC, respectively). 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 Erlang Multirate Loss Model [48] and the retry loss models [49][50][51].…”