Precoding Optimization for Faster-Than-Nyquist Signaling With Probabilistic Shaping

Kang, Weimin; Che, Hui; Zhu, Kun

doi:10.1109/tvt.2020.3011711

Cited by 6 publications

(13 citation statements)

References 31 publications

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“…The MC with PAS has a 2.0 dB gain compared with the DC at the approximately equal SE. The MC with PAS has a 0.2 dB gain compared with the PS4 (the DC with PAS) in [27] at the approximately equal SE.…”

Section: Ber Resultsmentioning

confidence: 93%

“…a is a sequence of non-uniformly distributed (shaped) symbols according to the probability distribution P (a). The shaped symbols a are represented by binary labels, i.e., b = χ −1 (|a|), where χ −1 is the inverse function of χ (|•|) and χ (|•|) represents the amplitude label operation [27]. The binary labels b and the data bits u A are encoded by a binary LDPC encoder.…”

Section: System Modelmentioning

confidence: 99%

“…The LDPC code is systematic to preserve the distribution of the shaped symbols. c is the check bit sequence of LDPC and the sign sequence d = χ −1 u A , c , where χ −1 is the inverse function of χ (•) and χ (•) means the sign label operation [27]. If the length of a is large enough, the total code rate [24]…”

Section: System Modelmentioning

confidence: 99%

“…Wu and Kang in [26] have improved the PAS with a time-sharing method. We have employed the PAS for FTN with DC [27]. Jana et al in [15] have employed the PAS for MFTN with DC.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the FTN-LPE achieves the precoding gain in addition to the compression gain. Che et al [11], [27] have optimized the convolution precoder for the FTN with DC. We ignored the effects of inter-frame interference to evaluate the information-theoretic limit and achievable BER limit of the coded modulation system.…”

Section: Introductionmentioning

confidence: 99%

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Multicarrier Faster-Than-Nyquist Based on Efficient Implementation and Probabilistic Shaping

2021

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The conventional multicarrier faster-than-Nyquist (MFTN) achieves the spectral efficiency (SE) gain by deep compression. However, deep compression leads to severe intersymbol interference (ISI) or intercarrier interference (ICI). We propose the MFTN based on efficient implementation and probabilistic amplitude shaping (PAS) to achieve the SE gain with low complexity. We use mild compression instead of conventional deep compression to achieve the compression gain. The MFTN transceiver with the mild compression can be efficiently implemented by fast Fourier transform (FFT)/inverse FFT (IFFT) and filtering operation. The linear pre-equalization (LPE) method eliminates the ISI for mild compression. The MFTN with efficient implementation employs PAS to achieve extra shaping gain. The theoretical results and simulation results show that our method can achieve better performance than the conventional FTN/MFTN with deep compression. The proposed method does not require a complex equalization algorithm and global turbo iteration so that the total complexity is reduced.INDEX TERMS Multicarrier, faster-than-Nyquist, linear pre-equalization, probabilistic shaping, mild compression.

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Section: Ber Resultsmentioning

confidence: 93%

Section: System Modelmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

“…Wu and Kang in [26] have improved the PAS with a time-sharing method. We have employed the PAS for FTN with DC [27]. Jana et al in [15] have employed the PAS for MFTN with DC.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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