2021
DOI: 10.1109/tvt.2021.3071511
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A Computationally Lightest and Robust Neural Network Receiver for Ultra Wideband Time Hopping Communication Systems

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Cited by 7 publications
(5 citation statements)
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“…Subsequently, in 2000, Win and Scholtz employed TH-PPM as an approach for ultra-wideband (UWB) communication. Then the Federal Communications Commission (FCC) in 2002 allocated a substantial frequency band to UWB, rendering it freely available [ 10 , 11 , 12 , 13 , 14 , 15 ]. This development enabled the integration of UWB into the civilian sector, with TH-PPM emerging as a vital means within this landscape in the subsequent years [ 16 , 17 , 18 , 19 , 20 , 21 ].…”
Section: Introductionmentioning
confidence: 99%
“…Subsequently, in 2000, Win and Scholtz employed TH-PPM as an approach for ultra-wideband (UWB) communication. Then the Federal Communications Commission (FCC) in 2002 allocated a substantial frequency band to UWB, rendering it freely available [ 10 , 11 , 12 , 13 , 14 , 15 ]. This development enabled the integration of UWB into the civilian sector, with TH-PPM emerging as a vital means within this landscape in the subsequent years [ 16 , 17 , 18 , 19 , 20 , 21 ].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, the GatedNet and the computational lightest receiver based on the multilayer perceptron (MLP) neural network have been proposed for TH-IR UWB systems in [133] and [134], respectively. These neural networks are trained using noiseless samples, which avoids the concerns about the noise model or training SNR to maintain good performance in online detection.…”
Section: Chapter 4 An Orientational Beamforming System Based On the R...mentioning
confidence: 99%
“…In order to reduce computational complexity and training time, the number of hidden layers is kept small (usually ≤3) in existing neural network receivers for UWB systems [134]. Compared with the fully connected DNN or MLP neural network, the radial basis function (RBF) neural network is more attractive in some situations due to its fewer parameters to be trained [135].…”
Section: Chapter 4 An Orientational Beamforming System Based On the R...mentioning
confidence: 99%
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