TY - GEN
T1 - Grant-Free Uplink Transmission in Self-Powered IoT Networks
AU - Gharbieh, Mohammad
AU - ElSawy, Hesham
AU - Yang, Hong-Chuan
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2019
Y1 - 2019
N2 - Ambient radio frequency (RF) energy harvesting is widely promoted as an enabler for self-powered wireless networks. This paper jointly characterizes the harvested energy and the packet transmission success probability in grant-free uplink IoT networks energized via harvesting downlink energy. To do that, a joint queueing theory and stochastic geometry model is exploited and a spatiotemporal analytical model is developed accordingly. Particularly, the harvested energy and packet transmission success probability are characterized using tools from stochastic geometry. Moreover, each device is modeled using a two-dimensional discrete-time Markov chain (DTMC) to track the time evolution of the joint states of the scavenged energy and the data buffer. Consequently, the adopted queueing model represents the devices as spatially interacting queues. To that end, the network performance is assessed in light of the packet throughput, the average waiting time, and the average buffer size which offer valuable insights for network design.
AB - Ambient radio frequency (RF) energy harvesting is widely promoted as an enabler for self-powered wireless networks. This paper jointly characterizes the harvested energy and the packet transmission success probability in grant-free uplink IoT networks energized via harvesting downlink energy. To do that, a joint queueing theory and stochastic geometry model is exploited and a spatiotemporal analytical model is developed accordingly. Particularly, the harvested energy and packet transmission success probability are characterized using tools from stochastic geometry. Moreover, each device is modeled using a two-dimensional discrete-time Markov chain (DTMC) to track the time evolution of the joint states of the scavenged energy and the data buffer. Consequently, the adopted queueing model represents the devices as spatially interacting queues. To that end, the network performance is assessed in light of the packet throughput, the average waiting time, and the average buffer size which offer valuable insights for network design.
UR - http://hdl.handle.net/10754/661917
UR - https://ieeexplore.ieee.org/document/9013334/
UR - http://www.scopus.com/inward/record.url?scp=85081972387&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM38437.2019.9013334
DO - 10.1109/GLOBECOM38437.2019.9013334
M3 - Conference contribution
SN - 9781728109626
BT - 2019 IEEE Global Communications Conference (GLOBECOM)
PB - IEEE
ER -