Wideband Spectrum Sensing Using Modulated Wideband Converter and Data Reduction Invariant Algorithms
Sensors, 2023 Wideband spectrum sensing is a challenging problem in the framework of cognitive radio and spectrum surveillance, mainly because of the high sampling rates required by standard approaches.
Gilles Burel +3 more
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Design of a Single Channel Modulated Wideband Converter for Wideband Spectrum Sensing: Theory, Architecture and Hardware Implementation [PDF]
Sensors, 2017 In a cognitive radio sensor network (CRSN), wideband spectrum sensing devices which aims to effectively exploit temporarily vacant spectrum intervals as soon as possible are of great importance.
Weisong Liu +3 more
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Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter [PDF]
Sensors, 2016 The modulated wideband converter (MWC) is a kind of sub-Nyquist sampling system which is developed from compressed sensing theory. It accomplishes highly accurate broadband sparse signal recovery by multichannel sub-Nyquist sampling sequences.
Ziyong Xu, Zhi Li, Jian Li
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Broadband Spectrum Sensing of Distributed Modulated Wideband Converter Based on Markov Random Field
ETRI Journal, 2018 The Distributed Modulated Wideband Converter (DMWC) is a networking system developed from the Modulated Wideband Converter, which converts all sampling channels into sensing nodes with number variables to implement signal undersampling.
Zhi Li, Jiawei Zhu, Ziyong Xu, Wei Hua
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A Modulated Wideband Converter Model Based on Linear Algebra and Its Application to Fast Calibration
Sensors, 2022 In the context of cognitive radio, smart cities and Internet-of-Things, the need for advanced radio spectrum monitoring becomes crucial. However, surveillance of a wide frequency band without using extremely expensive high sampling rate devices is a ...
Gilles Burel +2 more
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Wideband spectrum sensing based on modulated wideband converter with nested array [PDF]
IET Communications, 2021 Several spectrum sensing systems based on sub‐Nyquist sampling have been extensively studied to deal with difficulties of traditional wideband spectrum sensing in cognitive radio (CR) networks.
Qiuyue Li, Zhi Li, Jian Li
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An Effective Reconstruction Algorithm Based on Modulated Wideband Converter for Wideband Spectrum Sensing [PDF]
IEEE Access, 2020 In recent years, wideband spectrum sensing combined with sub-Nyquist sampling and compressed sensing technology in the field of cognitive radio has received widespread attention.
Jiai He, Wei Chen, Lu Jia, Tong Wang
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IEEE Access, 2018 Wideband spectrum sensing is an important aspect of cognitive radio systems. In current models of wide spectrum sensing, a discrete frequency denotes a continuous frequency band. This type of model is divorced from practice and cannot reflect the reality
Yulong Gao, Yanping Chen, Yongkui Ma
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Theoretical Analysis of Noise Figure for Modulated Wideband Converter [PDF]
IEEE Transactions on Circuits and Systems I: Regular Papers, 2020 The Modulated Wideband Converter (MWC) is one of the promising sub-Nyquist sampling architectures for sparse wideband signal sensing, cognitive radio applications and so on. In order to design an MWC-based RF receiver that meets a target RF specification, noise figure (NF) of the MWC has to be well-defined by its design properties.
Iizuka Tetsuya +2 more
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Relevant Support Recovery Algorithm in Modulated Wideband Converter [PDF]
IET Communications, 2019 Modulated wideband converter (MWC) is a compressed spectrum sensing system that randomly moves the sparse wideband signal spectrum to the baseband to realise low‐speed sampling. Then, obtaining the effective support which is based on compressed sensing is the most important part for the signal recovery from samples.
Zhi Li
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