Speed based Linear Power allocation in Small Cell Networks

Small cell networks promise good Quality of Service (QoS) even for cell edge users, however pose challenges to cater for high-speed users. The major difficulty being that of frequent handovers and the corresponding handover losses, which significantly depend upon the speed of the user. It is shown previously that the optimal cell size increases with speed. Thus in scenarios with diverse users (speeds spanning over large ranges), it would be inefficient to serve all users using common cell radius and it is practically infeasible to design different cell sizes for different speeds. We alternatively propose to allocate power to a user based on its speed. Higher power virtually increases the cell size. We solve well known Hamiltonian Jacobi equations under certain assumptions to obtain a power law, optimal for busy probability, for any given average power constraint and cell size. The optimal power allocation turns out to be linear in speed. We built a system level simulator for small cell network, using elaborate Monte-carlo simulations, and show that the performance of the system improves significantly with linear power law. The power law is tested even for the cases where system does not satisfy the assumptions required by theory. We observed good improvements in almost all cases, an improvement up to 80% is noted for certain configurations. Thus we conclude that the speed based linear power allocation would provide good improvement in drop probability