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A multi-tier network architecture for long distance rural wireless networks in developing regions

Today, in spite of technological advances, large disparities still exist between the industrialized world and the developing world. Information and communication technologies, in particular, have immense potential to provide better health, education and economic opportunities to people in the developing world, but most currently available communication solutions are often not financially viable in rural areas. 
We believe that wireless infrastructure that starts off by offering connectivity to targeted locations is the most practical way to extend communication coverage to rural areas. To that end, we propose WiLDNet, a new multi-tier network architecture composed of high-bandwidth long-distance point-to-point backbone wireless links and medium-distance point-to-multipoint access links. We also propose to use cheap and widely available off-the-shelf WiFi-based radios as the base technology to build this architecture. Unfortunately, standard WiFi radios suffer from low throughput, high packet loss rates and poor spectrum efficiency in the real world long-distance environments. 
In this dissertation, we demonstrate the feasibility of the WiLDNet architecture. We first characterize the underlying problems behind the poor performance of WiFi in long-distance scenarios. To overcome these problems, we build WiLDMAC, a novel time-division based MAC-layer that increases channel utilization and eliminates packet collisions at long distances. To achieve high end-to-end multi-hop throughput in the point-to-point backbone of our architecture, we use a combination of ARQ and FEC-based loss recovery mechanisms. Our measurements show 2–5 fold improvement in throughput on single-hop links as long as 382km. To achieve high capacity scaling and to support dynamic traffic demands in the point-to-multipoint part of our architecture, we implement and evaluate three techniques—(a) dynamic power adaptation to minimize interference and maximize spectrum usage; (b) dynamic channel width adaptation to increase the number of simultaneous clients; and (c) physical antenna combination to decrease the cost of installation of base-stations. 
Finally, we deploy our long-distance wireless links in several real world networks. Our rural telemedicine network in Aravind Eye Hospitals, India that connects ten village clinics, has already enabled 90,000 remote video consultations, showed operational sustainability and is in the process of expanding coverage to treat 500,000 people/year.