Dissertation Defense - Bonface Ogutu Osoro - Department of Geography and Geoinformation Science

PhD Candidate: Bonface Ogutu Osoro 

PhD of Science, Earth Systems and Geoinformation Sciences

Department of Geography and Geoinformation Science 

Dissertation Title: A Geospatial Techno-Economic Terrestrial and Satellite Broadband Model for Connecting the Unconnected Poverty-Line Population. 

Dissertation Chair: Dr. Edward J. Oughton (GMU, Geography and Geoinformation Science) 

Committee Members: 

Dr. Dr. Konrad Wessels (GMU, Geography and Geoinformation Science) 

Dr. Chaowei Yang (GMU, Geography and Geoinformation Science) 

Dr. Luis Ortiz (GMU, Department of Atmospheric, Oceanic & Earth Sciences) 

Abstract: 
Sub -Saharan Africa (SSA) is one of the regions with the highest coverage gaps (number of people uncovered by mobile signal). Providing universal coverage is key to unlocking economic potential of such regions and even addressing second order effects such as poverty and inequality. However, addressing coverage gap requires detailed knowledge of the population number and distribution to design effective and sustainable broadband solutions. To this end, this dissertation presents open-source techno-economic geospatial models for addressing the connectivity problem in SSA. The model is a framework of evaluating the number of people uncovered by mobile broadband and living below the poverty line in areas of different population density thresholds (deciles 1 to 10). The model is applied to assess the viability of three broadband technologies (mobile, fiber and satellites) in connecting 16 million people who are living below US$ 1.9 a day and uncovered by 3G cellular signal. 

A demand model for quantifying the unconnected and poor population is first presented. It is estimated that over 225 million people in 44 SSA countries are living below US$ 1.9 a day in areas with a population density of less than 106 people per km2. A mobile broadband model is thus developed to compare the capacity, cost and environmental emissions of connecting these populations using 4G or 5G systems. The results revealed that 4G is more viable in providing broadband to areas with over 36 people per km2 but 5G is only limited to regions with at least 958 people per km2. 

An innovative low-cost fixed fiber architecture is also designed to bring fiber close to areas inhabited by 550 million people (48% of the total SSA population). Using Geographical Information Systems (GIS) spatial optimization approach, two algorithms are presented. The Minimum Spanning Tree (MST) and Prize-Collecting Steiner Tree (PCST) algorithms are used to design the least cost fixed fiber network closer to the settlements before quantifying the cost and resultant environmental impacts. The results revealed that it will cost US$ 26-67 billion (3.3% of SSA GDP) to bring fiber closer to the population living in areas with over 106 people per km2. Furthermore, deployment of fiber closer to people in these areas will result in 3.1-20 Mt CO2 e (2.4% of the total greenhouse gas emissions in SSA). 

In addition to mobile broadband and fixed fiber, the study assessed the viability of Low Earth Orbit (LEO) satellite systems. Three LEO systems (Starlink, OneWeb and Kuiper) were assessed to determine the average capacity, cost and emissions per user for serving the frontier population especially in areas with a population density of less than 21 people per km2. It was estimated that in areas with less than 9 people per km2, the average total cost of deploying LEO per person amounted to US$ 59 (Starlink), US$ 97 (OneWeb), and US$ 61 (Kuiper). Similarly, the associated annualized per user emission values were 357 kg CO2 e (Starlink), 830 kg CO2 e (OneWeb), and 578 kg CO2 e (Kuiper). These results underscored the affordability and environmental complexity of serving remote populations. 

Ultimately, a set of recommendations including market-driven approach, state-driven approach and LEO driven solutions are proposed to bridge the digital divide in SSA using either of the three technologies. The recommendations are based on the population density and affordability of broadband in the areas. The affordability is based on the UN broadband commission’s suggestion that the cost of connectivity should be less than 2% of the average monthly Gross Domestic Income (GNI) per capita.