Low-Complexity Coding, Modulation and Pulse Shaping for SkyCubesNet CubeSat Transceivers

CubeSats present a promising opportunity to meet the rapidly increasing demand on high-speed connectivity. The SkyCubesNet project aims to establish a CubeSat constellation over Qatar and Turkey that provides high-speed connectivity over urban and rural areas to serve individual users and support sm...

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Vydané v:International Wireless Communications and Mobile Computing Conference (Online) s. 1412 - 1417
Hlavní autori: Zeedan, Amr, Khattab, Tamer
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 19.06.2023
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ISSN:2376-6506
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Shrnutí:CubeSats present a promising opportunity to meet the rapidly increasing demand on high-speed connectivity. The SkyCubesNet project aims to establish a CubeSat constellation over Qatar and Turkey that provides high-speed connectivity over urban and rural areas to serve individual users and support smart cities infrastructure. Nevertheless, establishing high-speed connectivity with CubeSats requires groundbreaking solutions to overcome the obstacles associated with designing low-power high-speed transceivers at the size and mass requirements of CubeSats. Demodulation and channel decoding are known to be two of the most computationally extensive tasks of any transceiver. In this paper, we develop a low-complexity channel coding and modulation scheme suitable for CubeSats based on Low Density Parity Check (LDPC) coding and Differential Binary Phase Shift Keying (DBPSK). We propose a low-complexity LDPC decoding algorithm that can support high-throughput applications at low implementation cost. It is found that at a bit error rate of 10^{-6} the coded system signal to noise ratio (SNR) requirement is 4\mathrm{~dB} lower than that of the uncoded system. Moreover, the performance improvement of the coded system increases with increasing SNR. The paper presents evaluation of the system's performance and implementation cost. Compared with similar works on CubeSat transceivers, our system has the highest data rate, highest code rate, and lowest number of decoding iterations.
ISSN:2376-6506
DOI:10.1109/IWCMC58020.2023.10182996