The Internet of things (IoT) advancement relies on connecting a huge number of sensors that are inexpensive, simple structured and self-powered.
Global Navigation Satellite Systems (GNSS), including GPS, GLONASS, Galileo or BeiDou, are used in many applications, most notably tracking the position and attitude (or orientation) of a vehicle or any moving platform.
Advanced sensor networks are needed in order to meet the increasing needs of IoT applications, such as automated surveillance, environmental monitoring, smart cities, and so on. Optimal sensor placement, i.e., to select the best subset of sensing locations out of a large set of available locations, keeping in mind the network infrastructure and the inference task, forms an important sensor network design task.
Oceans, which occupy 97% of planet Earth surface, produce numerous benefits to humankind, e.g., food supply, climate regulation, recreation, transportation, and medicine. Nevertheless, 95% of oceans remains unexplored, which necessitates deploying underwater wireless sensor networks (UWSNs), as a means to explore oceans and reserve their bio-diversity.
By exploiting large antenna arrays, massive multiple-input multiple-output (MIMO) systems can greatly increase spectral and energy efficiency over traditional MIMO systems.