Doppler‐robust high‐spectrum‐efficiency VCM‐OFDM scheme for low Earth orbit satellites broadband data transmission

Li, Jionghui; Xiong, Wenjing; Sun, Geng; Wang, Zhugang; Huang, Yonghui; Shen, Ming

doi:10.1049/iet-com.2017.0229

Cited by 8 publications

(5 citation statements)

References 13 publications

(13 reference statements)

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“…Generally, when the elevation angle of a LEO satellite is greater than 5 • , the transmission link is established [13], as shown in Fig. 2.…”

Section: A Time-varying Signal Powermentioning

confidence: 99%

“…4. On the other hand, the LEO satellite-to-ground transmission link is simply modeled as a point-to-point AWGN channel due to the negligible multi-path fading [13]. Hence, free-space path loss (FSPL) is the main contribution to the transmission loss in LEO satellite-to-ground communication.…”

Section: A Time-varying Signal Powermentioning

confidence: 99%

“…Hence, free-space path loss (FSPL) is the main contribution to the transmission loss in LEO satellite-to-ground communication. The FSPL is the attenuation of the radio energy, which depends on the signal wavelength and the transmission distance, and is defined as [13] F SP L(dB) = 10 log…”

Section: A Time-varying Signal Powermentioning

confidence: 99%

“…The Doppler frequency shift can be compensated by both analog and digital methods [13], [16], [17]. In this paper, we assume an ideal compensation of the Doppler frequency shift before the DSR model.…”

Section: B Time-varying Doppler Frequencymentioning

confidence: 99%

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A Digital Signal Recovery Technique Using DNNs for LEO Satellite Communication Systems

Zhang

Wang

Huang

et al. 2021

IEEE Trans. Ind. Electron.

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This paper proposes a new digital signal recovery (DSR) technique for next-generation power efficient low Earth orbit (LEO) satellite-to-ground communication systems, which feature additive white Gaussian noise (AWGN) channel and significant power variation. This technique utilizes the prior knowledge (i.e., nonlinearities of radio frequency power amplifiers (RF-PAs)) of space-borne transmitters to improve the quality of the signal received at ground stations by modeling and mitigating the imperfection using deep neural networks (DNNs). Benefiting from its robustness against noise and power variation, the proposed DNN based DSR technique (DNN-DSR), can correct high signal distortions caused by the nonlinearities and hence allows RF-PAs to work close to their saturation region, leading to a high power efficiency of the LEO satellites. This work has been validated by both simulations and experiments, in comparison with the power backoff technique as well as memory polynomial based DSR solutions. Experimental results show that the DNN-DSR technique can increase the drain efficiency of the spaceborne RF-PA from 32.6% to 45% while maintaining the same error vector magnitude as the power back-off technique. It has also been demonstrated that the proposed DNN-DSR technique can handle a signal power variation of 12 dB, which is challenging for conventional solutions.

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“…Generally, when the elevation angle of a LEO satellite is greater than 5 • , the transmission link is established [13], as shown in Fig. 2.…”

Section: A Time-varying Signal Powermentioning

confidence: 99%

Section: A Time-varying Signal Powermentioning

confidence: 99%

Section: A Time-varying Signal Powermentioning

confidence: 99%

Section: B Time-varying Doppler Frequencymentioning

confidence: 99%

See 2 more Smart Citations

A Digital Signal Recovery Technique Using DNNs for LEO Satellite Communication Systems

Zhang

Wang

Huang

et al. 2021

IEEE Trans. Ind. Electron.

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show abstract

“…Content may change prior to final publication. modeled as a point-to-point additive white Gaussian noise (AWGN) channel [6], [15]. Moreover, because of the fast motion of LEO satellites, the LEO satellite-to-ground communication channel features a wide and rapid time-varying Doppler frequency shift and received signal power.…”

Section: Imperfections Of Leo Satellite-to-ground Communicationsmentioning

confidence: 99%

Deep Neural Network-Based Receiver for Next-Generation LEO Satellite Communications

et al. 2020

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ICI and BEP analysis of hyperbolic FRFT based systems for satellite internet of things

2020

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Doppler‐robust high‐spectrum‐efficiency VCM‐OFDM scheme for low Earth orbit satellites broadband data transmission

Cited by 8 publications

References 13 publications

A Digital Signal Recovery Technique Using DNNs for LEO Satellite Communication Systems

A Digital Signal Recovery Technique Using DNNs for LEO Satellite Communication Systems

Deep Neural Network-Based Receiver for Next-Generation LEO Satellite Communications

ICI and BEP analysis of hyperbolic FRFT based systems for satellite internet of things

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