TY - GEN
T1 - An Accurate Channel Prediction Method for Massive MIMO-Based LEO Communications
AU - Liu, Zhiqiang
AU - Guo, Jingjing
AU - Zhang, Di
AU - Su, Yuwei
AU - Sato, Takuro
N1 - Funding Information:
Research, Development and Promotion Project under grant 212102210175; the Henan Provincial Key Scientific Research Project for College and University under grant: 21A510011; the Henan Key Laboratory of Network Cryptography Technology under grant LNCT2021-A06.
Funding Information:
VI. ACKNOWLEDGEMENT This study was supported by the National Science Fundation of China under grant 62001423; the Henan Provincial Key
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - As a promising component of the beyond fifth gener-ation (B5G) and forthcoming sixth generation (6G), massive multi-ple input multiple output (massive MIMO)-based low earth orbit (LEO) communication is facing unprecedented serious doppler frequency shifts and delays due to its fast relative moving speed between the transmitters and receivers, which makes the accurate channel state information (CSI) hard to obtain. In order to solve this problem, we introduce an improved channel prediction method, named Prony-based spatial-delay domain (SDD-Prony) prediction, it not only achieves an accurate CSI acquisition for fast-speed relative motion massive MIMO-based LEO commu-nications, but also greatly reduces the computational complexity. Besides, we find that the prediction error of our method converges to zero when the number of antennas and bandwidth growing large, provided that only two sufficiently accurate channel samples are needed. The validness of our theoretical analysis is verified by numerical results, and the simulations also further demonstrate the effectiveness of our method.
AB - As a promising component of the beyond fifth gener-ation (B5G) and forthcoming sixth generation (6G), massive multi-ple input multiple output (massive MIMO)-based low earth orbit (LEO) communication is facing unprecedented serious doppler frequency shifts and delays due to its fast relative moving speed between the transmitters and receivers, which makes the accurate channel state information (CSI) hard to obtain. In order to solve this problem, we introduce an improved channel prediction method, named Prony-based spatial-delay domain (SDD-Prony) prediction, it not only achieves an accurate CSI acquisition for fast-speed relative motion massive MIMO-based LEO commu-nications, but also greatly reduces the computational complexity. Besides, we find that the prediction error of our method converges to zero when the number of antennas and bandwidth growing large, provided that only two sufficiently accurate channel samples are needed. The validness of our theoretical analysis is verified by numerical results, and the simulations also further demonstrate the effectiveness of our method.
KW - Prony's method
KW - channel prediction
KW - fast-speed moving
KW - low earth orbit communications
KW - massive MIMO
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U2 - 10.1109/IWCMC55113.2022.9824991
DO - 10.1109/IWCMC55113.2022.9824991
M3 - Conference contribution
AN - SCOPUS:85135337843
T3 - 2022 International Wireless Communications and Mobile Computing, IWCMC 2022
SP - 702
EP - 707
BT - 2022 International Wireless Communications and Mobile Computing, IWCMC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Wireless Communications and Mobile Computing, IWCMC 2022
Y2 - 30 May 2022 through 3 June 2022
ER -