Faster-than-Nyquist signaling: on linear and non-linear reduced-complexity turbo equalization

Abelló, Albert; Roque, Damien; Freixe, Jean-Marie; Mallier, Sébastien

doi:10.1007/s10470-017-0937-z

Cited by 4 publications

(2 citation statements)

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“…also characterized, for example in [50,184]. Moreover, FTN signaling has been applied to several specific scenarios other than microwave communications, such as optical communications [47, 130, 137, 139-141, 158, 185-193], digital video broadcast [160,[194][195][196][197], the 5G cellular backhaul [198] and visible light communications [199].…”

Section: E Other Ftn Transceiver Architectures and Applicationsmentioning

confidence: 99%

The Evolution of Faster-Than-Nyquist Signaling

2021

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The fifty-year progress of faster-than-Nyquist (FTN) signaling is surveyed. FTN signaling exploits non-orthogonal dense symbol packing in the time domain for the sake of increasing the data rate attained. After reviewing the system models of both the conventional Nyquist-based and FTN signaling transceivers, we survey the evolution of FTN techniques, including their low-complexity detection and channel estimation. Furthermore, in addition to the classic FTN signaling philosophy, we introduce the recent frequency-domain filtering and precoding aided schemes. When relying on precoding, the information rate of FTN signaling becomes related to the eigenvalues of an FTN-specific intersymbol interference matrix, which provides a unified framework for the associated information-theoretic analysis and simplifies the associated power allocation specifically designed for increasing the information rate attained. We show that the FTN signaling scheme combined with bespoke power allocation employing a realistic raised-cosine shaping filter achieves the Shannon capacity associated with ideal rectangular shaping filters.

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Section: E Other Ftn Transceiver Architectures and Applicationsmentioning

confidence: 99%

The Evolution of Faster-Than-Nyquist Signaling

2021

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“…Unfortunately, the additional algorithmic complexity induced has delayed the implementation of FTN systems for several decades. Iterative equalization and decoding techniques [5,19] combined with increasing computational capabilities have renewed the interest in FTN signaling, enabling spectral efficiency gains up to 8-20 % [12,15,14,10,1].…”

Section: Introductionmentioning

confidence: 99%

Blind Symbol Rate Estimation of Faster-than-Nyquist Signals Based on Higher-Order Statistics

Abelló

Roque

Freixe

2018

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Both faster-than-Nyquist (FTN) and cognitive radio go towards an efficient use of spectrum in radio communications systems at the cost of an added computational complexity at the receiver side. To gain the maximum potential from these techniques, non-data-aided receivers are of interest. In this paper, we use fourth-order statistics to perform blind symbol rate estimation of FTN signals. The estimator shows good performance results for moderate system's densities beyond the Nyquist rate and for a reasonable number of received samples.

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