Grant-Free Opportunistic Uplink Transmission in Wireless-Powered IoT: A Spatio-Temporal Model

Ambient radio frequency (RF) energy harvesting is widely promoted as an enabler for wireless-power Internet of Things (IoT) networks. This article jointly characterizes and packet transmissions in grant-free opportunistic uplink IoT networks energized via downlink energy. To do that, a joint queuing theory stochastic geometry model utilized to develop spatio-temporal analytical model. Particularly, the harvested transmission success probability are characterized using tools from geometry. Moreover, each device modeled two-dimensional discrete-time Markov chain (DTMC). Such two dimensions track scavenged/depleted to/from batteries along with arrival/departure packets devices buffers over time. Consequently, adopted represents spatially interacting queues. that end, network performance assessed light throughput, average delay, buffer size. The effect base stations (BSs) densification discussed several design insights provided. results show parameters power control channel access should be optimized maximize hence, minimize delay.