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Compressed Wideband Sensing in Cooperative Cognitive Radio Networks
2008
IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference
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This paper develops a distributed compressed spectrum sensing approach for (ultra-)wideband CR networks. ...
Meanwhile, spectral estimates from multiple local CR detectors are fused to collect spatial diversity gain, which improves the sensing quality especially under fading channels. ...
It is of interest to investigate the impact of the channel knowledge on spectrum sensing quality, yet the sensing techniques we will develop are applicable for both cases, based on the general expression ...
doi:10.1109/glocom.2008.ecp.721
dblp:conf/globecom/Tian08
fatcat:egqyevw7hvcvvngbds36qlcdpe
Special issue on compressive sensing in communications
2012
Physical Communication
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Compressive sensing, also known as compressive sampling, has made a tremendous impact on signal processing and statistical learning, and has facilitated numerous applications in areas ranging from medical ...
From data compression in band-limited systems to estimation of communication channels that are naturally sparse; from active or passive delay, angle, and Doppler estimation of specific targets to distributed ...
The paper [10] , ''Compressive Sampling based Differential Detection for UWB Signals'', investigates the design of ultra-wideband (UWB) impulse radio receivers, for which compressive sampling is particularly ...
doi:10.1016/j.phycom.2011.11.003
fatcat:w6az3zbrvzetjppj4sarld57ly
Application of Compressive Sensing in Cognitive Radio Communications: A Survey
2016
IEEE Communications Surveys and Tutorials
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Compressive Sensing (CS) has received much attention in several fields such as digital image processing, wireless channel estimation, radar imaging, and Cognitive Radio (CR) communications. ...
Starting with the basic principles and the main features of CS, it provides a classification of the main usage areas based on the radio parameter to be acquired by a wideband CR. ...
WSS
Wideband Spectrum Sensing
DCS
Distributed Compressive Sensing
WSN
Wireless Sensor Network
DR
Dynamic Range
QoS
Quality of Service
FC
Fusion Centre
UWB
Ultra-Wideband
FFT
Fast Fourier ...
doi:10.1109/comst.2016.2524443
fatcat:qvil3rvugzfnlpvpuf5nuklk6m
Wideband Cognitive Radio Networks Based Compressed Spectrum Sensing: A Survey
2018
Journal of Signal and Information Processing
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The task of sensing is becoming more challenging especially at wideband spectrum scenario. ...
Recently, compressive sensing introduced itself as a pioneer solution that relaxed the wideband sampling rate requirements. ...
Conventional estimation methods based on Nyquist sampling are challenging task in wideband spectrum. ...
doi:10.4236/jsip.2018.92008
fatcat:uxre4m3lfzcqpkvlbeokm33rou
Phase recovery for time of arrival estimation in the presence of interference
2015
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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In this paper, we introduce a compressive sensing scheme which recovers both corrupted samples and phase offsets between sub-bands. ...
Wide bandwidths reduce the impact of multipath propagation, but frequently results in interference from other devices. ...
One key issue not addressed in other work [11] is the recovery of the phase offset between channel estimates in different frequency bands. ...
doi:10.1109/icassp.2015.7178750
dblp:conf/icassp/NguyenHHL15
fatcat:kdzgablsarfqdfffihceqeotpq
An Efficient Wideband Spectrum Sensing Algorithm for Unmanned Aerial Vehicle Communication Networks
2019
IEEE Internet of Things Journal
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Experiment results showed increased efficiency of the proposed algorithm over existing compressive spectrum sensing algorithms. ...
Compressive sensing is applied in the cognitive radio to boost the performance of spectrum sensing. ...
The work of Wenbo Xu, Shu Wang and Shu Yan was supported by the National Natural Science ...
doi:10.1109/jiot.2018.2882532
fatcat:ivoyth64ijg33jtr64rh7tyvoy
A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed
2009
Sensors
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The goal of this paper is a tutorial treatment of wideband cognitive radio and radar-a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications ...
) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms-revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio ...
A Compressed Sensing Based Ultra-Wideband System The concept of the compressed sensing based UWB system is illustrated in Figure 26 . ...
doi:10.3390/s90806530
pmid:22454598
pmcid:PMC3312458
fatcat:3hljqkjzxvgpfh5vue5gbdk65q
A Signal Recovery Method Based on Bayesian Compressive Sensing
2019
Mathematical Problems in Engineering
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BCS-CW), is proposed to eliminate the impact of crawling waves using Bayesian compressive sensing. ...
To conclude, an experimental environment is designed in this paper and a method using the Ultra-Wideband (UWB) Local Positioning System II (UWB LPS), called Bayesian Compressed Sensing-Crawling Waves ( ...
Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper.
Acknowledgments ...
doi:10.1155/2019/7235239
fatcat:ng2fpuzb7jfodaqajkkzjkzzzq
A Survey of Wideband Spectrum Sensing Algorithms for Cognitive Radio Networks and Sub-Nyquist Approaches
[article]
2020
arXiv
pre-print
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To achieve higher data rates while maintaining high quality of service QoS, effective wideband spectrum sensing routines are crucial due to their capability of achieving spectral awareness over wide frequency ...
This article gives a survey of various wideband spectrum sensing approaches outlining their advantages and limitations; special attention is paid to approaches that utilise sub-Nyquist sampling techniques ...
They are customarily based on minimising the 2 Euclidean norm of the recovery error. ...
arXiv:2001.02574v1
fatcat:y5ooiavl7nbcxcx5l7744jeezi
Compressive sensing: From theory to applications, a survey
2013
Journal of Communications and Networks
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Sparsity, an inherent characteristic of many natural signals, enables the signal to be stored in few samples and subsequently be recovered accurately, courtesy of compressive sensing. ...
Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much more efficient way than the established Nyquist Sampling Theorem. ...
C.Ultra Wideband Systems In the emerging technology of Ultra Wideband (UWB) communication, compressive sensing plays a vital role by reducing the high data-rate of ADC at receiver [90] . ...
doi:10.1109/jcn.2013.000083
fatcat:mlxbvwfxivbubdbtzkqxgx5c3y
Distributed Compressive Sensing Augmented Wideband Spectrum Sharing for Cognitive IoT
2018
IEEE Internet of Things Journal
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In this paper, we propose a blind joint sub-Nyquist sensing scheme by utilizing the surround IoT devices to jointly sample the spectrum based on the multi-coset sampling theory. ...
knowledge of the number of occupied channels and signal-to-noise ratios. ...
Problem Formulation According to the general CS-based spectrum sensing framework shown in Fig. 2 , we know that the spectrum recovery performance would have direct impact on the sensing results. ...
doi:10.1109/jiot.2018.2837891
fatcat:cqeoq5duoja3hmjoqkp3etgffy
Near-Field Wideband Channel Estimation for Extremely Large-Scale MIMO
[article]
2022
arXiv
pre-print
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In this way, the entire wideband XL-MIMO channel can be recovered by compressed sensing algorithms. ...
Prior works either neglect the accurate near-field channel model or fail to exploit the beam split effect, resulting in poor channel estimation accuracy for wideband XL-MIMO. ...
Thus it can be recovered by compressed sensing (CS) based algorithms with low pilot overhead. ...
arXiv:2212.08401v1
fatcat:j5sop5sfpjfpbnr6eba42nryz4
Sparse Channel Modelling Using Multi-Measurement Vector Compressive Sensing
2018
2018 IEEE Global Communications Conference (GLOBECOM)
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of time-domain channels using single-measurement-vector compressive sensing algorithms. ...
Compressive sensing (CS) provides a powerful tool for sparse channel modelling and estimation. ...
Such channels are known as one type of ultra wideband channels. ...
doi:10.1109/glocom.2018.8648115
dblp:conf/globecom/CuiZLGZ18
fatcat:mbvoheq6e5du5feswqstujl5mq
Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems
2021
Sensors
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Second, potential RL and DL applications for different MIMO issues, such as detection, classification, and compression; channel estimation; positioning, sensing, and localization; CSI acquisition and feedback ...
This article focuses on RL and DL techniques for MIMO systems by presenting a comprehensive review on the integration between the two areas. ...
A joint design of channel estimator and pilot signal based on data-driven DL methodology for wideband Ma-MIMO systems are designed in [157] . ...
doi:10.3390/s22010309
pmid:35009848
pmcid:PMC8749942
fatcat:2w4th63dtrdyboa6rmhr5rcvja
Achieving Autonomous Compressive Spectrum Sensing for Cognitive Radios
2016
IEEE Transactions on Vehicular Technology
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In this paper, an autonomous compressive spectrum sensing (ACSS) framework is presented that enables a CR to automatically choose the number of measurements while guaranteeing the wideband spectrum recovery ...
Compressive sensing (CS) technologies present many advantages over other existing approaches for implementing wideband spectrum sensing in cognitive radios (CRs), such as reduced sampling rate and computational ...
will have significant impact on the performance of compressive spectrum sensing. ...
doi:10.1109/tvt.2015.2408258
fatcat:ljsv5cnekrboldhr73zrc3t42u
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