TY - JOUR
T1 - Comparing Aerial-RIS- and Aerial-Base-Station-Aided Post-Disaster Cellular Networks
AU - Matracia, Maurilio
AU - Kishk, Mustafa Abdelsalam
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2023-09-26
PY - 2023/9/22
Y1 - 2023/9/22
N2 - Reconfigurable intelligent surface (RIS) technology and its integration into existing wireless networks have recently attracted much interest. While an important use case of said technology consists in mounting RISs onto unmanned aerial vehicles (UAVs) to support the terrestrial infrastructure in post-disaster scenarios, the current literature lacks an analytical framework that captures the networks' topological aspects. Therefore, our study borrows stochastic geometry tools to estimate both the average and local coverage probability of a wireless network aided by an aerial RIS (ARIS); in particular, the surviving terrestrial base stations (TBSs) are modeled by means of an inhomogeneous Poisson point process, while the UAV is assumed to hover above the disaster epicenter. Our framework captures important aspects such as the TBSs' altitude, the fact that they may be in either line-of-sight or non-line-of-sight condition with a given node, and the Nakagami- m fading conditions of wireless links. By leveraging said aspects we accurately evaluate three possible scenarios, where TBSs are either: (i) not aided, (ii) aided by an ARIS, or (iii) aided by an aerial base station (ABS). Our selected numerical results reflect various situations, depending on parameters such as the environment's urbanization level, disaster radius, and the UAV's altitude.
AB - Reconfigurable intelligent surface (RIS) technology and its integration into existing wireless networks have recently attracted much interest. While an important use case of said technology consists in mounting RISs onto unmanned aerial vehicles (UAVs) to support the terrestrial infrastructure in post-disaster scenarios, the current literature lacks an analytical framework that captures the networks' topological aspects. Therefore, our study borrows stochastic geometry tools to estimate both the average and local coverage probability of a wireless network aided by an aerial RIS (ARIS); in particular, the surviving terrestrial base stations (TBSs) are modeled by means of an inhomogeneous Poisson point process, while the UAV is assumed to hover above the disaster epicenter. Our framework captures important aspects such as the TBSs' altitude, the fact that they may be in either line-of-sight or non-line-of-sight condition with a given node, and the Nakagami- m fading conditions of wireless links. By leveraging said aspects we accurately evaluate three possible scenarios, where TBSs are either: (i) not aided, (ii) aided by an ARIS, or (iii) aided by an aerial base station (ABS). Our selected numerical results reflect various situations, depending on parameters such as the environment's urbanization level, disaster radius, and the UAV's altitude.
UR - http://hdl.handle.net/10754/694622
UR - https://ieeexplore.ieee.org/document/10261452/
U2 - 10.1109/ojvt.2023.3316117
DO - 10.1109/ojvt.2023.3316117
M3 - Article
SN - 2644-1330
SP - 1
EP - 15
JO - IEEE Open Journal of Vehicular Technology
JF - IEEE Open Journal of Vehicular Technology
ER -