Experimental results based on offline processing reported at optical conferences
increasingly rely on neural network-based equalizers for accurate data recovery. However …

We propose a bi-directional gated recurrent unit neural network based nonlinear equalizer
(bi-GRU NLE) for coherent optical communication systems. The performance of bi-GRU NLE …

We present a new layer in which dynamic (ie, input-dependent) Infinite Impulse Response
(IIR) filters of order two are used to process the input sequence prior to applying …

Fiber-wireless integration has been widely studied as a key technology to support radio
access networks in sixth-generation wireless communication, empowered by artificial …

In this paper, a novel fully-connected deep neural network (FC-DNN)-based receiver is
proposed and experimentally demonstrated in an underwater wireless optical …

In this paper, a joint equalization and decoding method based on recurrent neural networks
(RNNs) is proposed for trellis coded modulation (TCM) systems. For traditional methods …

We leverage the supervised and semi-supervised Volterra nonlinear equalizers (VNLE) to
mitigate the system nonlinearity. Two methods are employed to estimate the coefficients …

In this work, for the first time to the best of our knowledge, we introduce the iterative pruning
technique into the transfer learning (TL) of neural network equalizers (NNE) deployed in …

The demand for high-speed data transmission has increased rapidly over the past few
years, leading to advanced optical communication techniques. However, most of machine …

An equalization scheme employing convolutional neural networks (CNN) is proposed in
generalized frequency division multiplexing (GFDM) for propagation in a hybrid microwave …