Blind equalization algorithms for dual-mode CAP-QAM reception

Garth, L.M.; Yang, Jian; Werner, Jean-Jacques

doi:10.1109/26.911453

Cited by 35 publications

(20 citation statements)

References 12 publications

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“…For square QAM constellations, MMA equalization [26,27] is an efficient blind method for constellation recovery which is more cost effective and does not require retraining after sudden channel changes, since the optical channel is not highly time varying. Square QAM constellations are rotationally symmetric by the angle π/2 (π for DBPSK).…”

Section: B Timing Recoverymentioning

confidence: 99%

Multi-band CAP for Next-Generation Optical Access Networks Using 10-G Optics

Wei

2018

J. Lightwave Technol.

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Section: B Timing Recoverymentioning

confidence: 99%

Multi-band CAP for Next-Generation Optical Access Networks Using 10-G Optics

Wei

2018

J. Lightwave Technol.

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“…Following filter pairs matched to the transmitter shaping filter pairs are used to separate the sub-band signals. Afterwards, the signal is resampled to two samples per symbol, which facilitates the implementation of a simple blind 14-tap T/2 spaced (T is the symbol time period) MMA algorithm based feed-forward equalizer (FFE) [17]. The equalized complex sub-band symbols are then converted into bits by the following differential QAM decoders.…”

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confidence: 99%

56 Gb/s multi-band CAP for data center interconnects up to an 80 km SMF

et al. 2016

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“…In the following the five main blind equalization algorithms are introduced, the error signal for each algorithm is defined as in [2]- [5]: -where â(n) is the slicer output , yor(n) and yoi(n) are the real and imaginary parts of yo(n) respectively, K1 and K2 are constants, R is the modulus defined in [2] and A,B are parameters defined as :…”

Section: Conventional Blind Equalizationmentioning

confidence: 99%

A New Blind Equalization Algorithm for Improving the Channel Equalized Performance

Badran¹

2017

ijecs

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Adaptive channel equalization accomplished without a training sequence is known as blind equalization. The decision directed algorithm (DDA), Godard algorithm (GA), Sato algorithm (SA), Benveniste and Goursat algorithm (BGA), and the stop-and-go algorithm (SNGA), are examples of Blind equalization techniques. These algorithms exhibit very slow convergence rates when compared to algorithms employed in conventional data equalization schemes. In order to speed up their convergence process, a modified algorithm (MA) can be employed which uses a combination of DDA and GA. The modified algorithm has demonstrated their effectiveness compared to other conventional techniques especially in the noisy environment. Keyword: LE, DFE, blind equalization, adaptive equalization algorithms. IntroductionAn equalizer is necessary when the inter-symbol interference (ISI) component of a channel output becomes large relative to the signal component and causes a high symbol error rate (SER). Some equalizers filter the channel outputs directly in order to present the decision slicer with a reduced ISI estimated symbol sequence. Other synthesize an output sequence using a channel estimate and the knowledge of the symbol alphabet, and search for the closest match to the actual channel output sequence.

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Blind equalization algorithms for dual-mode CAP-QAM reception

Cited by 35 publications

References 12 publications

Multi-band CAP for Next-Generation Optical Access Networks Using 10-G Optics

Multi-band CAP for Next-Generation Optical Access Networks Using 10-G Optics

56 Gb/s multi-band CAP for data center interconnects up to an 80 km SMF

A New Blind Equalization Algorithm for Improving the Channel Equalized Performance

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