GMSK Demodulation Combining 1D‐CNN and Bi‐LSTM Network Over Strong Solar Wind Turbulence Channel

Zhu, Man-Qin; Hu, Shengbo; Yang, Kai; Yan, Tingting; Ye, Lv; Li, Hongjuan; Jin, Yang

doi:10.1029/2022rs007438

Cited by 5 publications

(5 citation statements)

References 34 publications

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“…Age and height were the second and third factors respectively. Whether the core values match or not is not an important factor for most people to reject the pursuit of Friends of the opposite sex [4][5][6].…”

Section: Figure 3 the Reasons For Rejecting The Pursuit Of The Opposi...mentioning

confidence: 99%

Current Situation on Making Friends Among Tsinghua Graduate Students

Wang

2023

EHSS

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Emotional friendship is an integral part of people's lives. The analysis of people's behavior of make friends can help us better understand the behavioral characteristics of a certain group. However, there is currently no relevant research on the special group of highly educated doctors students from Tsinghua University (THU). It is not clear whether this group is consistent with the general emotional friendship habits and friendship status in the society, and what characteristics are there. This study investigated 46 PhD students at Tsinghua University by means of questionnaires, including different grades, different genders, and different genders. The study found that PhD students in THU remained more positive and optimistic in the evaluation of self-state, and at the same time became more depressed in their willingness to make friends. This brought serious anxiety. The study also found that the participants prefer to make friends through offline activities rather than through targeted online activities. We will start with the questionnaire survey, analyze the problems in this area from the perspective of probability, and finally come up with some general guidelines for making friends. Finally, we can let the audience know the novel overview of Tsinghua doctors, the high-knowledge group, on the emotional aspect.

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Section: Figure 3 the Reasons For Rejecting The Pursuit Of The Opposi...mentioning

confidence: 99%

Current Situation on Making Friends Among Tsinghua Graduate Students

Wang

2023

EHSS

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“…Study [13] proposes the use of a one-dimensional convolutional network with recurrent elements of long short-term memory for signal processing with Gaussian two-position frequency manipulation under conditions of strong disturbances caused by the solar wind.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…Works [12,13] show a certain potential of using one-dimensional convolutional networks for digital signal processing. However, in these works, only the operation of the proposed models with such types of modulation, where there are only two symbols, is demonstrated.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…To validate the effectiveness of the improved mathematical model of the artificial neural network, it will be advisable to conduct testing on a large set of signal fragments. The same set of fragments was also preprocessed with a reference model, which is equivalent to a real receiving device working with AMMC [12,13]. The main evaluation criterion is the number of false identifications of symbols during signal processing.…”

Section: Development Of a Validation Algorithm And Evalu Ation Of The...mentioning

confidence: 99%

“…It is the task similar to signal demodulation and decoding that is performed by models [12,13]. However, these models work with such types of digital modulation that have only 2 symbols.…”

Section: Conflicts Of Interestmentioning

confidence: 99%

See 2 more Smart Citations

Approach to processing radio signals with amplitude modulation of many components using one-dimensional convolutional neural network

Tsymbaliuk,

Horbatyi

2023

EEJET

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The object of research is the methods of using one-dimensional convolutional neural networks in radio receiving systems in order to increase their interference resistance. The task of the research is to test the hypothesis about the likely higher efficiency of radio signal recognition under conditions of high noise (or weak signals) by neural network models of radio signal reception in comparison with trivial reception systems. With the use of one-dimensional convolutional neural networks, a higher efficiency of extracting useful information from a signal-noise mixture at sufficiently high noise levels and, accordingly, a higher accuracy of radio signal recognition accuracy has been achieved. This result was achieved due to the specific architecture of convolutional neural networks, the ability to automatically detect important patterns in the data and analyze radio signals more deeply and informatively. Hierarchical representation of data with the selection of more complex and abstract features of the signal as the convolutional neural models become more complicated is one of the main advantages of using the proposed methods and algorithms under complex conditions of radio signal transmission. The comparison with trivial methods of radio signal processing is performed on the basis of the symbol error probability parameter at different signal-to-noise ratios of the investigated signals and demonstrates a stable decrease in the symbol error probability at signal-to-noise ratios of less than 4 dB. The results could be used in real radio communication systems, especially under conditions where it is necessary to quickly and reliably recognize radio signals among noise, under conditions of interference or with weak signals. They could also be useful in military applications, Earth remote sensing systems, mobile communication networks, etc.

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Channel Estimation for Deep Space Communications Under the Effect of Solar Scintillation

Xu,

Cai,

et al. 2024

Radio Science

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During probe‐to‐Earth superior conjunction, deep space communication channels will suffer from solar scintillation, leading to amplitude attenuation of received signals. This study aims to obtain the channel state information (CSI) on deep space channels affected by solar scintillation. Classical least squares (LS) and minimum mean squared error (MMSE) methods are adopted to perform channel estimation and compensate for the channel fading. Simulation results indicate that under the effect of solar scintillation, performing channel estimation technology can significantly improve bit error rate (BER) performance compared to systems without CSI, and the MMSE algorithm outperforms the LS for both BER and normalized mean squared error (NMSE). In addition, we also find that pilot density, geometric parameters, and the outer scale of solar wind turbulence has great influence on the estimation performance.

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GMSK Demodulation Combining 1D‐CNN and Bi‐LSTM Network Over Strong Solar Wind Turbulence Channel

Cited by 5 publications

References 34 publications

Current Situation on Making Friends Among Tsinghua Graduate Students

Current Situation on Making Friends Among Tsinghua Graduate Students

Approach to processing radio signals with amplitude modulation of many components using one-dimensional convolutional neural network

Channel Estimation for Deep Space Communications Under the Effect of Solar Scintillation

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