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Found 7 papers, 0 papers with code
CNN-Based Equalization for Communications: Achieving Gigabit Throughput with a Flexible FPGA Hardware Architecture
Thus, in this work, we present a high-performance FPGA implementation of an ANN-based equalizer, which meets the throughput requirements of modern optical communication systems.
Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications
In this work, we present a high-throughput field programmable gate array (FPGA) demonstrator of an artificial neural network (ANN)-based equalizer.
Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks
We demonstrate and evaluate a fully-blind digital signal processing (DSP) chain for 100G passive optical networks (PONs), and analyze different equalizer topologies based on neural networks with low hardware complexity.
Unsupervised ANN-Based Equalizer and Its Trainable FPGA Implementation
In recent years, communication engineers put strong emphasis on artificial neural network (ANN)-based algorithms with the aim of increasing the flexibility and autonomy of the system and its components.
A Hybrid Approach combining ANN-based and Conventional Demapping in Communication for Efficient FPGA-Implementation
In communication systems, Autoencoder (AE) refers to the concept of replacing parts of the transmitter and receiver by artificial neural networks (ANNs) to train the system end-to-end over a channel model.
Blind and Channel-agnostic Equalization Using Adversarial Networks
The proposed approach is independent of the equalizer topology and enables the application of powerful neural network based equalizers.
HALF: Holistic Auto Machine Learning for FPGAs
To efficiently implement DNNs on a specific FPGA platform for a given cost criterion, e. g. energy efficiency, an enormous amount of design parameters has to be considered from the topology down to the final hardware implementation.
