Performance Evaluation of a C-RAN Supporting Quasi-Random Traffic

In this paper we consider a cloud radio access network (C-RAN) where the remote radio heads (RRHs) are separated from the baseband signal processing servers, named baseband units (BBUs). The latter forms a centralized pool of high-performance data center resources. To benefit from network function virtualization, we consider virtualized BBU (V-BBU) resources where the BBU functionality and services have been virtualized in the form of virtual network functions. We consider all RRHs in the C-RAN as a single cluster. Each RRH of such a cluster accommodates quasi-random traffic. This means that new calls in a RRH are generated by a finite number of mobile users. An arriving call requires a radio resource unit from the serving RRH and a computational resource unit from the V-BBU. If these resource units are available, then the call is accepted and remains in the system for a generally distributed service time. Otherwise, the call is blocked and lost. In order to analyze this C-RAN we model it as a loss system, show that the steady probabilities have a product form solution and propose a convolution algorithm for the accurate determination of the main teletraffic performance measure which is congestion probabilities. The accuracy of this algorithm is verified via simulation.