Alexander is a graduate with an honors degree in Telecommunications Engineering from Makerere University and also currently pursuing a Masters of science in the same field at Makerere University. He has a demonstrated history of working in the telecommunications industry specifically in radio network planning and as a graduate researcher in netlabs!UG with skills in research and development (R&D) and data analytics. His research interests are broadly centered on mobile wireless communications with emphasis on energy efficient communication technologies designed to address the environmental impact of conventional communication systems and networks. He has participated in various service and outreach programs aimed at expanding ICT awareness and services in developing countries like Uganda. His future research prospects are geared towards enhancing existing approaches and developing novel ones for improving the quality of service of communications systems as an enabler for the country's sustainable growth.
My Publications / Research
Paper Presented at The 5th National Conference on Communications held in Kampala, Uganda, from 17th - 18th October 2019.
Paper Abstract: Over the last few years, traffic demand has increased exponentially and forecasts show that this trend will continue. Operators have to expand and upgrade their networks to provide the required capacity. As we head into the era of 5G, cellular networks will continue to become ever more heterogeneous in nature, characterized by a dense deployment of small cells. As base stations (BSs) become smaller, they enable more aggressive frequency reuse which results into enhanced capacity. In addition, location and deployment constraints on such cells reduce. It is envisaged that small BSs (sBSs) will be deployed easily on street furniture, simple poles, etc. When the physical locations options increase, the operator ought to pick the best locations for deployment. In this paper, we propose a location optimization algorithm that can be used to choose the best locations subject to a network capacity constraint. Our results show that when the algorithm is applied, the capacity targets can be achieved with few sBSs. In addition, the algorithm significantly enhances the energy efficiency (EE) of the dense heterogeneous network (HetNet).