Keywords :
3GPP; channel estimation; flexible payload; LEO; MEO; NGSO satellites; resource allocation; Channel dynamics; Channel prediction; Flexible payloads; NGSO satellite; Precoding designs; Resources allocation; Round-trip-time; Electrical and Electronic Engineering; Applied Mathematics; Signal Processing; Computer Science Applications
Abstract :
[en] The advanced payload technology has opened up a new way to design future NGSO satellite systems exploiting the full flexibility in radio resource and beam coverage management. Conventional spatial multiplexing techniques, which require the CSI, however, cannot be efficiently applied in NGSO due to long round-trip time(RTT). In this paper, we tackle the long RTT in the precoding design by proposing a joint channel prediction and dynamic radio resource management framework. Our aim is to optimize the bandwidth and transmit power in every spot beam based on the predicted channel gains to maximize the system capacity. Since the satellite's orbit is time-varying but predictable, Kalman filter-based channel estimation method is employed. Given the predicted channels, a joint bandwidth allocation and precoding design is formulated. The effectiveness of the proposed framework is demonstrated via practical satellite channel models using the STK software and 3GPP codebook- and non-codebook-based precoding designs.
Name of the research project :
U-AGR-7288 - C22/IS/17220888/RUTINE (01/09/2023 - 31/08/2026) - VU Thang Xuan
R-AGR-3929 - IPBG19/14016225/INSTRUCT - SES (01/10/2020 - 30/09/2026) - CHATZINOTAS Symeon
Funding text :
ACKNOWLEDGMENT This work is supported by the Luxembourg National Research Fund via project FNR RUTINE, ref. FNR/C22/IS/17220888/RUTINE, and project FNR INSTRUCT, ref. FNR/IPBG19/14016225/INSTRUCT.
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