82 citations · 101 across the 16 of their papers we have counts for
11 papers · 1 filter
FPGA-Based Experimental Analysis of Fixed-Point Precision Impact on SOP Estimation in Coherent Communications Receivers
Geraldo Gomes, Rafael Vieira, Hani Kbashi +8
We experimentally evaluated the sensing-communication trade-off from the fixed-point precision MIMO equalizer using FPGA. At 7-bit, noise floor drops 100x and angular error 63%, bu…
FPGA Implementation of Low-Power Multiplierless Pre-Processing Free Chromatic Dispersion Equalizer
Geraldo Gomes, Pedro Freire, Jaroslaw E. Prilepsky +1
We present a novel time-domain chromatic dispersion equalizer, implemented on FPGA, eliminating pre-processing and multipliers, achieving up to 54.3% energy savings over 80-1280 km…
FPGA Implementation of Complex Value-based Clustering Filter for Chromatic Dispersion Compensation in Coherent Metro Links with Ultra-low Power Consumption
Geraldo Gomes, Pedro Freire, Jaroslaw E. Prilepsky +1
This paper introduces a new machine learning-assisted chromatic dispersion compensation filter, demonstrating its superior power efficiency compared to conventional FFT-based filte…
Geometric Clustering for Hardware-Efficient Implementation of Chromatic Dispersion Compensation
Geraldo Gomes, Pedro Freire, Jaroslaw E. Prilepsky +1
Power efficiency remains a significant challenge in modern optical fiber communication systems, driving efforts to reduce the computational complexity of digital signal processing,…
Multi-Task Learning to Enhance Generalizability of Neural Network Equalizers in Coherent Optical Systems
Sasipim Srivallapanondh, Pedro J. Freire, Ashraful Alam +6
For the first time, multi-task learning is proposed to improve the flexibility of NN-based equalizers in coherent systems. A "single" NN-based equalizer improves Q-factor by up to…
Knowledge Distillation Applied to Optical Channel Equalization: Solving the Parallelization Problem of Recurrent Connection
Sasipim Srivallapanondh, Pedro J. Freire, Bernhard Spinnler +4
To circumvent the non-parallelizability of recurrent neural network-based equalizers, we propose knowledge distillation to recast the RNN into a parallelizable feedforward structur…