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Wideband Spectrum Sensing Using Modulated Wideband Converter and Data Reduction Invariant Algorithms [PDF]

open access: yesSensors, 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
doaj   +8 more sources

A Modulated Wideband Converter Model Based on Linear Algebra and Its Application to Fast Calibration [PDF]

open access: yesSensors, 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
doaj   +8 more sources

Design of a Single Channel Modulated Wideband Converter for Wideband Spectrum Sensing: Theory, Architecture and Hardware Implementation [PDF]

open access: yesSensors, 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
doaj   +8 more sources

Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter [PDF]

open access: yesSensors, 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
doaj   +8 more sources

Sparse-Bayesian-Learning-Based Wideband Spectrum Sensing With Simplified Modulated Wideband Converter

open access: yesIEEE 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
doaj   +5 more sources

Spectrum Sensing Using Co-Prime Array Based Modulated Wideband Converter [PDF]

open access: yesSensors, 2017
As known to us all, it is challenging to monitor wideband signals in frequency domain due to the restriction of hardware. Several practical sampling schemes, such as multicoset sampling and the modulated wideband converter (MWC), have been proposed.
Wanghan Lv, Wang Huali
exaly   +6 more sources

Wideband spectrum sensing based on modulated wideband converter with nested array [PDF]

open access: yesIET 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
doaj   +3 more sources

An Effective Reconstruction Algorithm Based on Modulated Wideband Converter for Wideband Spectrum Sensing [PDF]

open access: yesIEEE 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
doaj   +3 more sources

Theoretical Analysis of Noise Figure for Modulated Wideband Converter [PDF]

open access: yesIEEE 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,
Tetsuya Iizuka   +2 more
exaly   +3 more sources

Broadband Spectrum Sensing of Distributed Modulated Wideband Converter Based on Markov Random Field

open access: yesETRI 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
doaj   +3 more sources

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