TY - GEN
T1 - CE-Optimized Cross-Beam Combining for GEO Satellite in Space-Air-Ground Integrated Network
AU - Wu, Liangzi
AU - Zou, Yucong
AU - Wang, Shuai
AU - Tian, Buning
AU - Song, Zhe
AU - Miao, Xiaqing
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Geostationary Earth orbit (GEO) satellites constitute critical components in space-air-ground integrated network (SAGIN). This paper presents a cross-beam signal combining framework that leverages beam-overlapping regions using direct sequence spread spectrum (DSSS) in multi-beam GEO satellite systems. By synchronously transmitting identical information across multiple beams and performing coherent combining at the receiver, the proposed scheme effectively enhances the system's low-probability-of-detection (LPD) and anti-jamming capabilities. To mitigate phase offsets and channel gain mismatches caused by transponder non-idealities and beam-edge effects, a cross-entropy (CE)-optimized joint estimation algorithm is proposed for simultaneous estimation of multiple parameters across signal branches. Simulation results demonstrate that the proposed algorithm achieves notable improvements in signal-to-noise ratio (SNR), estimation accuracy, and computational efficiency, confirming its robustness and scalability.
AB - Geostationary Earth orbit (GEO) satellites constitute critical components in space-air-ground integrated network (SAGIN). This paper presents a cross-beam signal combining framework that leverages beam-overlapping regions using direct sequence spread spectrum (DSSS) in multi-beam GEO satellite systems. By synchronously transmitting identical information across multiple beams and performing coherent combining at the receiver, the proposed scheme effectively enhances the system's low-probability-of-detection (LPD) and anti-jamming capabilities. To mitigate phase offsets and channel gain mismatches caused by transponder non-idealities and beam-edge effects, a cross-entropy (CE)-optimized joint estimation algorithm is proposed for simultaneous estimation of multiple parameters across signal branches. Simulation results demonstrate that the proposed algorithm achieves notable improvements in signal-to-noise ratio (SNR), estimation accuracy, and computational efficiency, confirming its robustness and scalability.
KW - coherent combining
KW - cross-entropy
KW - joint multi-parameter estimation
KW - space-air-ground integrated network
UR - https://www.scopus.com/pages/publications/105034193254
U2 - 10.1109/ICCT67417.2025.11373968
DO - 10.1109/ICCT67417.2025.11373968
M3 - Conference contribution
AN - SCOPUS:105034193254
T3 - International Conference on Communication Technology Proceedings, ICCT
SP - 740
EP - 745
BT - 2025 IEEE 25th International Conference on Communication Technology, ICCT 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Communication Technology, ICCT 2025
Y2 - 16 October 2025 through 18 October 2025
ER -