An analysis of backhaul costs of radio access networks using stochastic geometry

A flexible and effectual back-haul infrastructure is required for managing extremely dense future mobile networks proficiently, and economically. This paper aims to establish a framework which can estimate the cost of a network, and then use the framework to minimize the deployment cost of the network by optimizing the number of back-haul nodes required to help the base stations satisfy user demands. The two main contributions of this work are: the derivation of a framework that gives the cost of deploying a back-haul node in a 3-layer model which consists of users, base stations, and back-haul nodes; and the generalization of the framework to obtain the cost of deploying a node in a particular layer of interest in a k-layer model. The utility of this framework is illustrated for the 3-layer model by showing that there exist a range of back-haul node intensity values for which deployment costs can be minimized while satisfying users' rate requirements.