TY - JOUR
T1 - A CSI Prediction Scheme for Satellite-Terrestrial Networks
AU - Chang, Guey Yun
AU - Hung, Chia Kai
AU - Chen, Chi Hao
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Recently, low Earth orbit (LEO) satellites have been suggested as a promising solution for global coverage of 5G networks. However, long propagation delay makes obtained channel state information (CSI) (which is employed for efficient spectrum utilization) outdated before usage. Note that CSI is closely related to elevation angle and relative location. Although elevation angle and relative location could be estimated by terrestrial device position and LEO ephemeris, maintaining these two informations requires a high cost for most IoT devices. Due to regular and high-speed orbital movement of LEO, for an arbitrary terrestrial device, LEOs repeat the same behavioral pattern (e.g., satellite rise and satellite set) again and again. Satellite rise and set result in different temporal correlations in elevation angle and relative location. By the aid of the temporal correlations mentioned above, we proposed a CSI prediction scheme for satellite-terrestrial networks without terrestrial device position and LEO ephemeris. Simulation results show that our scheme has a rather low prediction error under various LEO altitude/obit, terrestrial device location/mobility, ground environments, weather, and elevation angle when handover.
AB - Recently, low Earth orbit (LEO) satellites have been suggested as a promising solution for global coverage of 5G networks. However, long propagation delay makes obtained channel state information (CSI) (which is employed for efficient spectrum utilization) outdated before usage. Note that CSI is closely related to elevation angle and relative location. Although elevation angle and relative location could be estimated by terrestrial device position and LEO ephemeris, maintaining these two informations requires a high cost for most IoT devices. Due to regular and high-speed orbital movement of LEO, for an arbitrary terrestrial device, LEOs repeat the same behavioral pattern (e.g., satellite rise and satellite set) again and again. Satellite rise and set result in different temporal correlations in elevation angle and relative location. By the aid of the temporal correlations mentioned above, we proposed a CSI prediction scheme for satellite-terrestrial networks without terrestrial device position and LEO ephemeris. Simulation results show that our scheme has a rather low prediction error under various LEO altitude/obit, terrestrial device location/mobility, ground environments, weather, and elevation angle when handover.
KW - 5G network
KW - channel state information (CSI)
KW - recurrent neural network (RNN)
KW - satellite-terrestrial
UR - http://www.scopus.com/inward/record.url?scp=85154553376&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2022.3229683
DO - 10.1109/JIOT.2022.3229683
M3 - 期刊論文
AN - SCOPUS:85154553376
SN - 2327-4662
VL - 10
SP - 7774
EP - 7785
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 9
ER -