# On the Fronthaul Statistical Multiplexing Gain

## TL;DR

This paper analyzes how aggregating remote radio units in cloud radio access networks can statistically multiplex fronthaul capacity, reducing user blocking probability and improving scalability.

## Contribution

A tractable model is proposed to quantify fronthaul multiplexing gain and user blocking probability bounds in clustered C-RANs.

## Key findings

- User blocking probability decreases exponentially with capacity per RRU.
- Fronthaul multiplexing gain increases with cluster size.
- Significant multiplexing gain observed even at small to medium cluster sizes.

## Abstract

Breaking the fronthaul capacity limitations is vital to make cloud radio access network (C-RAN) scalable and practical. One promising way is aggregating several remote radio units (RRUs) as a cluster to share a fronthaul link, so as to enjoy the statistical multiplexing gain brought by the spatial randomness of the traffic. In this letter, a tractable model is proposed to analyze the fronthaul statistical multiplexing gain. We first derive the user blocking probability caused by the limited fronthaul capacity, including its upper and lower bounds. We then obtain the limits of fronthaul statistical multiplexing gain when the cluster size approaches infinity. Analytical results reveal that the user blocking probability decreases exponentially with the average fronthaul capacity per RRU, and the exponent is proportional to the cluster size. Numerical results further show considerable fronthaul statistical multiplexing gain even at a small to medium cluster size.