Extending the coverage of the internet of things with low-cost nanosatellite networks

Abstract Recent technology advances have made CubeSats not only an affordable means of access to space, but also promising platforms to develop a new variety of space applications. In this paper, we explore the idea of using nanosatellites as access points to provide extended coverage to the Internet of Things (IoT) and Machine-to-Machine (M2M) communications. This study is mainly motivated by two facts: on the one hand, it is already obvious that the number of machine-type devices deployed globally will experiment an exponential growth over the forthcoming years. This trend is pushed by the available terrestrial cellular infrastructure, which allows adding support for M2M connectivity at marginal costs. On the other hand, the same growth is not observed in remote areas that must rely on space-based connectivity. In such environments, the demand for M2M communications is potentially large, yet it is challenged by the lack of cost-effective service providers. The traffic characteristics of typical M2M applications translate into the requirement for an extremely low cost per transmitted message. Under these strong economical constraints, we expect that nanosatellites in the low Earth orbit will play a fundamental role in overcoming what we may call the IoT digital divide . The objective of this paper is therefore to provide a general analysis of a nanosatellite-based, global IoT/M2M network. We put emphasis in the engineering challenges faced in designing the Earth-to-Space communication link, where the adoption of an efficient multiple-access scheme is paramount for ensuring connectivity to a large number of terminal nodes. In particular, the trade-offs energy efficiency–access delay and energy efficiency–throughput are discussed, and a novel access approach suitable for delay-tolerant applications is proposed. Thus, by keeping a system-level standpoint, we identify key issues and discuss perspectives towards energy efficient and cost-effective solutions.

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