Towards 1 Gbps/UE in Cellular Systems: Understanding Ultra-Dense Small Cell Deployments

David Lopez-Perez, Ming Ding, Holger Claussen, Amir H. Jafari
2015 IEEE Communications Surveys and Tutorials  
Todays heterogeneous networks comprised of mostly macrocells and indoor small cells will not be able to meet the upcoming traffic demands. Indeed, it is forecasted that at least a 100x network capacity increase will be required to meet the traffic demands in 2020. As a result, vendors and operators are now looking at using every tool at hand to improve network capacity. In this epic campaign, three paradigms are noteworthy, i.e., network densification, the use of higher frequency bands and
more » ... ral efficiency enhancement techniques. This paper aims at bringing further common understanding and analysing the potential gains and limitations of these three paradigms, together with the impact of idle mode capabilities at the small cells as well as the user equipment density and distribution in outdoor scenarios. Special attention is paid to network densification and its implications when transitioning to ultra-dense small cell deployments. Simulation results show that network densification with an average inter site distance of 35 m can increase the cell- edge UE throughput by up to 48x, while the use of the 10GHz band with a 500MHz bandwidth can increase the network capacity up to 5x. The use of beamforming with up to 4 antennas per small cell base station lacks behind with cell-edge throughput gains of up to 1.49x. Our study also shows how network densifications reduces multi-user diversity, and thus proportional fair alike schedulers start losing their advantages with respect to round robin ones. The energy efficiency of these ultra-dense small cell deployments is also analysed, indicating the need for energy harvesting approaches to make these deployments energy- efficient. Finally, the top ten challenges to be addressed to bring ultra-dense small cell deployments to reality are also discussed.
doi:10.1109/comst.2015.2439636 fatcat:rjgl7ozogzgufmqxeuwwpfrkxu