Business case evaluations for LTE network offloading with cognitive femtocells

Mobile networks are increasingly becoming capacity limited such that more base stations and smaller cells or more spectrum are required to serve the subscribers’ increasing data usage. Among several challenges, the establishment of new base station sites becomes challenging and expensive. This study proposes and analyzes critical aspects of a business case where a mobile operator offloads its mobile LTE network by deploying cognitive femtocells. When aided by a sensor network the cognitive femtocell will be able to use frequencies other than the mobile network and hence increase its power to cover outdoor areas and neighbour buildings. This cognitive femtocell strategy will be compared with an alternative strategy where an operator deploys conventional femtocells and has to build additional base stations to meet the traffic demands. The business case analysis illustrates that there is a potential for cost savings when offloading the mobile network with cognitive femtocells when compared to the alternative strategy. It must be emphasized that the studied concept is innovative and that the business case period starts in 2017, hence, parameter assumptions are uncertain. Therefore, as the most important message of this work, sensitivity analysis is used to reveal the most critical aspects of the cognitive femtocell business case. It is found that the most critical parameters regarding the cognitive femtocell are the price for backhauling, the number of users supported and the coverage. Furthermore, an optimal coverage radius for the cognitive femtocell for lowest possible costs is found. Costs related to the fixed sensor network are found to be less critical since sensors are embedded in the cognitive femtocells. Sensitivity analysis is also presented for spectral efficiency, cognitive and conventional femtocell offloading gain, sensor density and price, customer density and price for base station site establishment.

► A business case is modelled for LTE network offloading with cognitive femtocells.
► The most critical parameter is backhauling costs for the cognitive femtocells.
► External sensor network costs are less critical when cognitive femtocells can sense.
► The number of supported users by the cognitive femtocell is a critical parameter.
► The optimal radius is found for the cognitive femtocell for lowest possible costs.