TY - JOUR
T1 - NOMA-Based Hybrid Satellite-UAV-Terrestrial Networks for 6G Maritime Coverage
AU - Fang, Xinran
AU - Feng, Wei
AU - Wang, Yanmin
AU - Chen, Yunfei
AU - Ge, Ning
AU - Ding, Zhiguo
AU - Zhu, Hongbo
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Current fifth-generation (5G) networks do not cover maritime areas, causing difficulties in developing maritime Internet of Things (IoT). To tackle this problem, we establish a nearshore network by collaboratively using on-shore terrestrial base stations (TBSs) and tethered unmanned aerial vehicles (UAVs). These TBSs and UAVs form virtual clusters in a user-centric manner. Within each virtual cluster, non-orthogonal multiple access (NOMA) is adopted for agilely including various maritime IoT devices, which are sparsely distributed over the vast ocean. The nearshore network also shares the spectrum with marine satellites. In such a NOMA-based hybrid satellite-UAV-Terrestrial network, interference among different network segments, different clusters, and different users occurs. We thereby formulate a joint power allocation problem to maximize the sum rate of the network. Different from existing studies, we use large-scale channel state information (CSI) only for optimization to reduce system overhead. The large-scale CSI is obtained by using the position information of maritime IoT devices. The problem is non-convex with intractable non-linear constraints. We tackle these difficulties by adopting max-min optimization, the auxiliary function method, and the successive convex approximation technique. An iterative power allocation algorithm is accordingly proposed, which is shown to be effective for coverage enhancement by simulations. This shows the potential of NOMA-based hybrid satellite-UAV-Terrestrial networks for maritime on-demand coverage.
AB - Current fifth-generation (5G) networks do not cover maritime areas, causing difficulties in developing maritime Internet of Things (IoT). To tackle this problem, we establish a nearshore network by collaboratively using on-shore terrestrial base stations (TBSs) and tethered unmanned aerial vehicles (UAVs). These TBSs and UAVs form virtual clusters in a user-centric manner. Within each virtual cluster, non-orthogonal multiple access (NOMA) is adopted for agilely including various maritime IoT devices, which are sparsely distributed over the vast ocean. The nearshore network also shares the spectrum with marine satellites. In such a NOMA-based hybrid satellite-UAV-Terrestrial network, interference among different network segments, different clusters, and different users occurs. We thereby formulate a joint power allocation problem to maximize the sum rate of the network. Different from existing studies, we use large-scale channel state information (CSI) only for optimization to reduce system overhead. The large-scale CSI is obtained by using the position information of maritime IoT devices. The problem is non-convex with intractable non-linear constraints. We tackle these difficulties by adopting max-min optimization, the auxiliary function method, and the successive convex approximation technique. An iterative power allocation algorithm is accordingly proposed, which is shown to be effective for coverage enhancement by simulations. This shows the potential of NOMA-based hybrid satellite-UAV-Terrestrial networks for maritime on-demand coverage.
KW - Hybrid satellite-UAV-Terrestrial network
KW - interference
KW - maritime Internet of Things
KW - non-orthogonal multiple access (NOMA)
KW - power allocation
UR - http://www.scopus.com/inward/record.url?scp=85135763025&partnerID=8YFLogxK
U2 - 10.1109/TWC.2022.3191719
DO - 10.1109/TWC.2022.3191719
M3 - Article
AN - SCOPUS:85135763025
SN - 1536-1276
VL - 22
SP - 138
EP - 152
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 1
ER -