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While global navigation satellite system (GNSS) technologies have always been the go-to solution for localization problems, they may not be the best choice for some Internet-of-Things (IoT) applications due to the incurred power consumption and cost. In this paper, we present an alternative satellite-based localization method exploiting the signature of Doppler shifts and angle-of-arrival measurements as seen by a low-Earth-orbit (LEO) satellite. We first derive the joint likelihood function of the measurements, which is represented as a combination of three Gaussian distributions. Then, we show that the maximum likelihood problem reduces to a more-efficient mean squared error minimization in the Gaussian case as inferred from real measurements we collected from low-Earth-orbit satellite using a tracking ground station. Thus, we propose utilizing a stochastic optimizer to search for the global minimum of the mean squared error, which represents the location of the ground IoT device as estimated by the satellite platform. The emulated results show that the IoT device localization, in such a realistic model, can be performed with sufficient accuracy for IoT applications.

With advancements in computer processing power and deep learning techniques, hyperspectral imaging is continually being explored for improved sensing applications in various fields. However, the high cost associated with such imaging platforms impedes their widespread use in spite of the availability of the needed processing power. In this paper, we develop a novel theoretical framework required for an open source ultra-low-cost hyperspectral imaging platform based on the line scan method suitable for remote sensing applications. Then, we demonstrate the design and fabrication of an open source platform using consumer-grade commercial off-the-shelf components that are both affordable and easily accessible to researchers and users. At the heart of the optical system is a consumer-grade spectroscope along with a basic galvanometer mirror that is widely used in laser scanning devices. The utilized pushbroom scanning method provides a very high spectral resolution of 2.8 nm, as tested against commercial spectral sensors. Since the resolution is limited by the slit width of the spectroscope, we also provide a deconvolution method for the line scan in order to improve the monochromatic spatial resolution. Finally, we provide a cost-effective testing method for the hyperspectral imaging platform where the results validate both the spectral and spatial performances of the platform.

Low Earth orbit (LEO) satellite constellations are currently being explored to provide global and seamless coverage for IoT-over-Satellite applications. Random access techniques require low transmission overhead providing a compatible route for IoT-over-Satellite applications, however, coming at the expense of the offered quality-of-service. In this paper, we develop a realistic uplink performance framework that incorporates many practical parameters such as the satellite availability, packet collision and interference, Doppler shift, and impairments experienced in a typical Satellite-to-Ground channel. The framework is capable of assessing multiple key performance indicators of the overall IoT-over-Satellite random access system. The performance is presented in terms of the bit error rate, packet error rate, and the energy wasted per IoT device. To emulate a realistic IoT-over-Satellite network, LoRa modulated traffic is first generated and injected into the Satellite-to-Ground channel. The results indicate high resistance to Doppler shifts even without any Doppler correction and provide some resistance to highly congested environments.

Delivering Internet-of-Things (IoT) connectivity over satellite is a promising solution for applications in remote and sparsely populated areas. These applications range from smart agriculture, logistics, asset tracking to emergency services. Using a shared radio spectrum with terrestrial services will facilitate a cost-effective and rapid deployment of IoT-over-Satellite since it reduces the administrative and financial hurdles of leasing a dedicated segment of the spectrum. Although IoT-over-Satellite communication provides larger service coverage, the vast number of IoT devices also increase the interference in the satellite uplink channel, and it becomes a significant challenge for the reliable performance of the IoT-over-satellite. In this paper, we propose a framework for modeling the performance of IoT-over-Satellite access systems when sharing the radio spectrum with terrestrial networks. We take into consideration several important aspects, namely; satellite orbit, terrestrial IoT devices uplink interference, atmosphere and gas absorption, and the probability of line-of-sight. The performance of the overall system is presented in terms of the uplink signal-to-interference-plus-noise ratio (SINR), and thus the time-availability of the satellite link during a typical pass. We focus on low earth orbit satellites due to their potential use in IoT applications, where we evaluate the framework using actual parameters of satellites located in 300–800 km orbits. Furthermore, the paper presents a numercial model to obtain the most suitable antenna beamwidth that maximizes the link-availability of the satellite link by the simultaneous reduction in the terrestrial interference and the boosting of the underlying IoT signal of interest.