An Approach for Narrow Band Interference Detection in Satellite Communication Using Morphological Filter

Hu, Jing; Bian, Dongming; Xie, Zhidong; Li, Yongqiang; Fan, Lehao

doi:10.2991/icitmi-15.2015.171

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…Some signals may be affected by other wireless communication systems on the ground and other satellites in the same frequency band, resulting interference in the same frequency. This paper uses the method described in [18] to detect and eliminate the narrow-band interference that may occur on the satellite spectrum. After the subband division on the satellite spectrum is completed, the signal parameters are estimated in each subband.…”

Section: Signal Subband Division and Signal Parameter Estimationmentioning

confidence: 99%

Design of a satellite spectrum detection method based on morphological iterative

Yang¹,

Wang²,

Zheng³

et al. 2023

International Conference on Optoelectronic Information and Functional Materials (OIFM 2023)

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Satellites are playing an increasingly irreplaceable role in communication systems. Aiming at the complex satellite spectrum environment, a satellite spectrum detection algorithm using morphological scale iterative filter to achieve noise floor estimation and adjusting the filtering threshold at each frequency point to filter out the noise base is proposed. The frequency band range of each signal is automatically divided according to the spectrum shape, and the interference caused by white noise and strong pulse to the measurement of signal center frequency and 3dB bandwidth parameter is reduced by cyclic smoothing. This method needs no prior information, and the noise base estimation is more accurate, realizing the detection of satellite spectrum and parameter measurement. The experimental simulation shows that the algorithm can effectively overcome the color noise and realize the spectrum detection and center frequency and bandwidth measurement.

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Section: Signal Subband Division and Signal Parameter Estimationmentioning

confidence: 99%

Design of a satellite spectrum detection method based on morphological iterative

Yang¹,

Wang²,

Zheng³

et al. 2023

International Conference on Optoelectronic Information and Functional Materials (OIFM 2023)

View full text Add to dashboard Cite

show abstract

“…Interference detection is a well-studied subject that has been addressed in the past few decades [146,147] , especially for satellite communication [145,148] .…”

Section: Definition and Limitationsmentioning

confidence: 99%

Artificial intelligence for satellite communication: A review

Fourati

Alouini

2021

Intell. and Converged Netw.

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Satellite communication offers the prospect of service continuity over uncovered and under-covered areas, service ubiquity, and service scalability. However, several challenges must first be addressed to realize these benefits, as the resource management, network control, network security, spectrum management, and energy usage of satellite networks are more challenging than that of terrestrial networks. Meanwhile, artificial intelligence (AI), including machine learning, deep learning, and reinforcement learning, has been steadily growing as a research field and has shown successful results in diverse applications, including wireless communication. In particular, the application of AI to a wide variety of satellite communication aspects has demonstrated excellent potential, including beam-hopping, anti-jamming, network traffic forecasting, channel modeling, telemetry mining, ionospheric scintillation detecting, interference managing, remote sensing, behavior modeling, space-air-ground integrating, and energy managing. This work thus provides a general overview of AI, its diverse sub-fields, and its state-of-the-art algorithms. Several challenges facing diverse aspects of satellite communication systems are then discussed, and their proposed and potential AI-based solutions are presented. Finally, an outlook of field is drawn, and future steps are suggested.

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“…Interference managing is a thus essential to preserve highquality and reliable communication systems; management includes detection, classification, and suppression of interference, as well as the application of techniques to minimize its occurrence. Interference detection is a well-studied subject that has been addressed in the past few decades [155], [156], especially for satellite communication [154], [157].…”

Section: F Ionospheric Scintillation Detectingmentioning

confidence: 99%

Artificial Intelligence for Satellite Communication: A Review

Fourati,

Alouini

2021

Preprint

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Satellite communication offers the prospect of service continuity over uncovered and under-covered areas, service ubiquity, and service scalability. However, several challenges must first be addressed to realize these benefits, as the resource management, network control, network security, spectrum management, and energy usage of satellite networks are more challenging than that of terrestrial networks. Meanwhile, artificial intelligence (AI), including machine learning, deep learning, and reinforcement learning, has been steadily growing as a research field and has shown successful results in diverse applications, including wireless communication. In particular, the application of AI to a wide variety of satellite communication aspects have demonstrated excellent potential, including beam-hopping, anti-jamming, network traffic forecasting, channel modeling, telemetry mining, ionospheric scintillation detecting, interference managing, remote sensing, behavior modeling, space-air-ground integrating, and energy managing. This work thus provides a general overview of AI, its diverse sub-fields, and its state-ofthe-art algorithms. Several challenges facing diverse aspects of satellite communication systems are then discussed, and their proposed and potential AI-based solutions are presented. Finally, an outlook of field is drawn, and future steps are suggested.

show abstract

An Approach for Narrow Band Interference Detection in Satellite Communication Using Morphological Filter

Cited by 4 publications

References 5 publications

Design of a satellite spectrum detection method based on morphological iterative

Design of a satellite spectrum detection method based on morphological iterative

Artificial intelligence for satellite communication: A review

Artificial Intelligence for Satellite Communication: A Review

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