2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech) 2019
DOI: 10.1109/eexpolytech.2019.8906884
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New Pulse Shapes for Partial Response Signaling to Outperform Faster-than-Nyquist Signaling

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Cited by 20 publications
(6 citation statements)
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“…The algorithm of ICA [24] combines proposed procedures for blind identification of the measured waveform. The mixing matrix corresponds to the partial pulse responses (PPR) [25] of the victim's signal and aggressor's signal. The independent components combine data, intersymbol interference (ISI), and crosstalk symbols.…”
Section: And Errormentioning
confidence: 99%
“…The algorithm of ICA [24] combines proposed procedures for blind identification of the measured waveform. The mixing matrix corresponds to the partial pulse responses (PPR) [25] of the victim's signal and aggressor's signal. The independent components combine data, intersymbol interference (ISI), and crosstalk symbols.…”
Section: And Errormentioning
confidence: 99%
“…In this correspondence, we employ a root-raised cosine (RRC) shaping pulse p(t) with a roll-off factor β. For other non-orthogonal signaling schemes [19]- [21], the shaping pulse p(t) can be adjusted and the following derivations are still valid.…”
Section: System Modelmentioning
confidence: 99%
“…Assume the value of maximum energy concentration in the occupied frequency bandwidth is equal to 99% [26], [28] of the whole energy of the finite-time signal in the infinite frequency bandwidth. Then, the optimization problem (2) can be given by:…”
Section: Ftn Signal Optimization By Conforming Criterion Of Maximmentioning
confidence: 99%
“…This optimization problem should have some constraints defined by the conditions for data transmitting over a continuous channel [22]- [25]. The criterion for the FTN signal shape optimization is based on the principle of choosing the maximum compactness degree of the energy spectrum of a random signal sequence, which is also called the criterion of the maximum energy concentration in the occupied frequency bandwidth ∆F [9], [26]. The occupied frequency bandwidth denoted as ∆F is determined by the concentration criterion of 99% of the signal's energy.…”
Section: Introductionmentioning
confidence: 99%