An 18-Gb/s NRZ Transceiver With a Channel-Included 2-UI Impulse-Response Filtering FFE and 1-Tap DFE Compensating up to 32-dB Loss

Ahn, Cheolmin; Hong, Jaehyeong; Shin, Jongshin; Kim, Byungsub; Park, Hong-June; Sim, Jae‐Yoon

doi:10.1109/tcsii.2020.2977931

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…It can be observed that the designed 3-tap FFE can optimize the eye-opening for all cable channels with −4.1/−6.6/−9.7-dB equalization. Table 1 summarizes the chip performance and compares this work with recent TXs [23][24][25][26] operating at a similar data rate and in a similar CMOS process. Our work shows a wider range of data rates, better energy efficiency, and wider eye width.…”

Section: Measurement Resultsmentioning

confidence: 99%

A 1.55-to-32-Gb/s Four-Lane Transmitter with 3-Tap Feed Forward Equalizer and Shared PLL in 28-nm CMOS

et al. 2021

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This paper presents a fully integrated physical layer (PHY) transmitter (TX) suiting for multiple industrial protocols and compatible with different protocol versions. Targeting a wide operating range, the LC-based phase-locked loop (PLL) with a dual voltage-controlled oscillator (VCO) was integrated to provide the low jitter clock. Each lane with a configurable serialization scheme was adapted to adjust the data rate flexibly. To achieve high-speed data transmission, several bandwidth-extended techniques were introduced, and an optimized output driver with a 3-tap feed-forward equalizer (FFE) was proposed to accomplish high-quality data transmission and equalization. The TX prototype was fabricated in a 28-nm CMOS process, and a single-lane TX only occupied an active area of 0.048 mm2. The shared PLL and clock distribution circuits occupied an area of 0.54 mm2. The proposed PLL can support a tuning range that covers 6.2 to 16 GHz. Each lane’s data rate ranged from 1.55 to 32 Gb/s, and the energy efficiency is 1.89 pJ/bit/lane at a 32-Gb/s data rate and can tune an equalization up to 10 dB.

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Section: Measurement Resultsmentioning

confidence: 99%

A 1.55-to-32-Gb/s Four-Lane Transmitter with 3-Tap Feed Forward Equalizer and Shared PLL in 28-nm CMOS

et al. 2021

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“…The proposed LSTM equalizer is a neural learning based signal equalizer without necessary to do signal pre-processing (FFE block). Current widely used solution for the transmission line signal recovering are general realized though DFE or FFE-DFE combination [31], [32], [33]. The LSTM addressed to a novel learning based equalizer which not only more suitable for high non-linear signal restore but adaptable for A deep learning based LSTM equalizer and corresponding implementation shows the effective of the deep LSTM equalizer for variable-frequency signal equalization.…”

Section: Discussionmentioning

confidence: 99%

“…There are three types of equalizers that are generally employed in the RX module. The feed-forward equalizer (FFE), the decision feedback equalizer (DFE) [5], [6], [7], and the continuoustime linear equalizer (CTLE) [8]. The FFE is dedicated to compensating the loss of the channel which is assumed to be an FIR filter with a transfer function inverse to the channel transfer function.…”

Section: Introductionmentioning

confidence: 99%

Long Short-Term Memory Neural Equalizer

Wang

et al. 2022

SSRN Journal

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A trainable neural equalizer based on Long Short-Term Memory (LSTM) neural network architecture is proposed in this paper to recover the channel output signal. The current widely used solution for the transmission line signal recovering is generally realized through DFE or FFE-DFE combination. The novel learning-based equalizer is suitable for highly non-linear signal restoration thanks to its recurrent design. The effectiveness of the LSTM equalizer is shown through an ADS simulation channel signal equalization task including a quantitative and qualitative comparison with an FFE-DFE combination. The LSTM neural network shows good equalization results compared to that of the FFE-DFE combination. The advantage of a trainable LSTM equalizer lies in its ability to learn its parameters in a flexible manner, to tackle complex scenario without any hardware modification. This can reduce the equalizer implantation cost for variant transmission channels and bring additional portability in practical applications.

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A 20-Gb/s charge-steering equalizer utilizing highly-efficient charge-steering linear equalizer

Saif

Hassan

Ibrahim

2021

Microelectronics Journal

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An 18-Gb/s NRZ Transceiver With a Channel-Included 2-UI Impulse-Response Filtering FFE and 1-Tap DFE Compensating up to 32-dB Loss

Cited by 8 publications

References 14 publications

A 1.55-to-32-Gb/s Four-Lane Transmitter with 3-Tap Feed Forward Equalizer and Shared PLL in 28-nm CMOS

A 1.55-to-32-Gb/s Four-Lane Transmitter with 3-Tap Feed Forward Equalizer and Shared PLL in 28-nm CMOS

Long Short-Term Memory Neural Equalizer

A 20-Gb/s charge-steering equalizer utilizing highly-efficient charge-steering linear equalizer

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