Cost optimization based network deployment strategies for future dense networks

Deploying dense small cell networks overlaying to the conventional macro cell networks is widely regarded as a key step towards network architecture revolution for improved coverage and user rate. Small cells have different kinds, and a target coverage can be achieved through deploying different kinds of small cells. Previous works mainly focus their attention on the optimization of spectrum and energy efficiency, which are less involved with the deployment cost and base station (BS) types. In this paper, we propose a theoretical methodology based on cost optimization to find the type and corresponding density of BS deployed using tools from stochastic geometry theory. Two cost optimization problems are formulated to obtain the optimal deployment cost which submitted to target user date rate (UDR) and coverage probability (CP) constraints. And the obtained equation of deployment cost provides insights on it can be affected by networking settings, such as BS density, user equipment (UE) density, BS transmit power and bandwidth. Based on the numerical simulation, we are able to find the optimal cell density and the corresponding optimal BS transmit power for achieving an optimal cost when other parameters are pre-setting.