Stochastic Geometry Analysis and Design of Wireless Powered MTC Networks

Abstract

Machine-type-communications (MTC) are being crucial in the development of next generation mobile networks. Given that MTC devices are usually battery constrained, wireless power transfer (WPT) and energy harvesting (EH) have emerged as feasible options to enlarge the lifetime of the devices, leading to wireless powered networks. In that sense, we consider a setup where groups of sensors are served by a base station (BS), which is responsible for the WPT. Additionally, EH is used to collect energy from the wireless signals transmitted by other sensors. To characterize the energy obtained from both procedures, we model the sporadic activity of sensors as Bernoulli random variables and their positions with repulsive Matérn cluster processes. This way, the random activity and spatial distribution of sensors are introduced in the analysis of the energy statistics. This analysis can be useful for system design aspects such as energy allocation schemes or optimization of idle-active periods, among others. As an example of use of the developed analysis, we include the design of a WPT scheme under a proportional fair policy.

Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach

“…The results showed a significant increase in network throughput due to the large number of connections from MTCDs. Unlike the above works, the authors in [19] used Matérn cluster processes to model the wireless-powered MTC networks.…”