2018
DOI: 10.1109/access.2017.2789185
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Cyclostationary Noise Mitigation for SIMO Powerline Communications

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Cited by 16 publications
(7 citation statements)
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References 31 publications
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“…The idea is to train a neural-network to project the noise time series in an appropriate latent space where the features can be extracted and used to classify the noise. In general, the exploitation of machine learning techniques can consistently aid the process of classification and the detection of noise classes in real noise scenarios [20], [32].…”
Section: A Classification and Generation Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The idea is to train a neural-network to project the noise time series in an appropriate latent space where the features can be extracted and used to classify the noise. In general, the exploitation of machine learning techniques can consistently aid the process of classification and the detection of noise classes in real noise scenarios [20], [32].…”
Section: A Classification and Generation Methodsmentioning
confidence: 99%
“…The noise in a MCO power line, in addition to the classes mentioned earlier, may manifest similar characteristics between different conductor pairs. An example is the high spatial correlation between the cyclostationary noise signals on different line phases, usually caused by network-based switched power supplies [32]. Moreover, measurements demonstrate that MCO noise is not only correlated but sometimes reveals deterministic behaviors [29].…”
Section: B the Deterministic Noisementioning
confidence: 99%
“…In [66], receiver strategies for CS noise reduction by using the FRESH filter approach are explained, they are applied to low SNR NB-PLC systems that implement OFDM. In [67], an improvement of the previous technique for CS noise mitigation designed with estimators also based on the FRESH filtering is discussed, with focus on PLC receivers of systems with single-input multiple-output.…”
Section: Plc System Design With Cyclic-aware Strategiesmentioning
confidence: 99%
“…In recent years, the cyclostationarity has been drawn great attention in the communication of signal processing [2], [3], such as blind source extraction [4], filtering [5], beamforming [6]. It has been shown that most of the man-made signals, e.g.…”
Section: Introductionmentioning
confidence: 99%