TY - JOUR
T1 - Underlay drone cell for temporary events
T2 - Impact of drone height and aerial channel environments
AU - Zhou, Xiaohui
AU - Durrani, Salman
AU - Guo, Jing
AU - Yanikomeroglu, Halim
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Providing seamless connection to a large number of devices is one of the biggest challenges for the Internet of Things (IoT) networks. Using a drone as an aerial base station (ABS) to provide coverage to devices or users on ground is envisaged as a promising solution for IoT networks. In this paper, we consider a communication network with an underlay ABS to provide coverage for a temporary event, such as a sporting event or a concert in a stadium. Using stochastic geometry, we propose a general analytical framework to compute the uplink and downlink coverage probabilities for both the aerial and the terrestrial cellular system. Our framework is valid for any aerial channel model for which the probabilistic functions of line-of-sight (LOS) and non-LOS links are specified. The accuracy of the analytical results is verified by Monte Carlo simulations considering two commonly adopted aerial channel models. Our results show the nontrivial impact of the different aerial channel environments (i.e., suburban, urban, dense urban, and high-rise urban) on the uplink and downlink coverage probabilities and provide design guidelines for best ABS deployment height.
AB - Providing seamless connection to a large number of devices is one of the biggest challenges for the Internet of Things (IoT) networks. Using a drone as an aerial base station (ABS) to provide coverage to devices or users on ground is envisaged as a promising solution for IoT networks. In this paper, we consider a communication network with an underlay ABS to provide coverage for a temporary event, such as a sporting event or a concert in a stadium. Using stochastic geometry, we propose a general analytical framework to compute the uplink and downlink coverage probabilities for both the aerial and the terrestrial cellular system. Our framework is valid for any aerial channel model for which the probabilistic functions of line-of-sight (LOS) and non-LOS links are specified. The accuracy of the analytical results is verified by Monte Carlo simulations considering two commonly adopted aerial channel models. Our results show the nontrivial impact of the different aerial channel environments (i.e., suburban, urban, dense urban, and high-rise urban) on the uplink and downlink coverage probabilities and provide design guidelines for best ABS deployment height.
KW - Aerial channel model
KW - Internet of Things (IoT)
KW - downlink
KW - stochastic geometry
KW - underlay drone cell
KW - uplink
UR - http://www.scopus.com/inward/record.url?scp=85054650445&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2018.2875166
DO - 10.1109/JIOT.2018.2875166
M3 - Article
SN - 2327-4662
VL - 6
SP - 1704
EP - 1718
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 2
M1 - 8488493
ER -