Wireless communication for sparse and rural areas
Wireless technology experienced a fast development in the past few decades. However, research and investment in wireless communication so far has been focused mainly on high-density domains or fully connected networks. The technologies/solutions developed for above domains do not readily apply to rural and sparse domains. The users in rural and sparse areas are still served predominantly by either low-speed dialup access or have no data service available at all. This research work explores the largely overlooked rural and sparse domains, where distance, rough terrain and low node density are the key parameters driving system design and performance, from the perspectives of fixed wireless applications to mobile wireless applications. For fixed wireless applications, a baseline wireless network structure for rural and sparse areas is defined and the potential for improved high-speed fixed communication services in rural and remote areas is examined. The potential of using multi-hop network topologies in very sparse areas is explored. The cost benefits of several other emerging technologies and approaches are also investigated with the objective of finding cost-effective and affordable high-speed broadband communications solutions for rural and remote areas.Mobile ad hoc networks (MANETs) are also examined as an approach to providing connectivity under conditions where fixed communications infrastructure is non-existent The unique characteristics of MANETs in rural areas are analyzed and a Geographic and Traffic Information based mobility model (GTI mobility model) is proposed to model mobile node movement under real world constraints. A Border node Based Routing (BBR) protocol is designed specifically for MANETs in rural areas. Simulation results show that the BBR routing protocol yields better performance than Dynamic Source Routing (DSR) when the network is partially connected and has comparable performance to DSR when the network is fully connected. BBR also has better performance than a Random Node Selection algorithm (RNS) when the network is partially connected. The results show that BBR can be applicable to a range of rural area applications including sparse vehicular ad hoc networks (VANETs) for public safety uses as well as a broader class of sparse ad hoc network applications where the nodes may exhibit a more random mobility pattern.