Browsing by Subject Optical communications

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  • Authors: Xiaoyu, Zhang; Thien Van, Luong; Periklis, Petropoulos;  Advisor: -;  Co-Author: - (2022)

    End-to-end learning systems are conceived for Orthogonal Frequency Division Multiplexing (OFDM)-aided optical Intensity Modulation paired with Direct Detection (IM/DD) communications relying on the Autoencoder (AE) architecture in deep learning. We first propose an AE-aided Layered ACO-OFDM (LACO-OFDM) scheme, termed as LACONet, for exploiting the increased bandwidth efficiency of LACO-OFDM. LACONet employs a Neural Network (NN) at the transmitter for bit-to-symbol mapping, and another NN at the receiver for recovering the data bits, which together form an AE and can be trained in an end-to-end manner for simultaneously minimizing both the BER and PAPR. Moreover, the detection archite...
  • Authors: Đào, Thanh Hải; Dao, Thanh Hai;  Advisor: -;  Co-Author: - (2020)

    Elastic optical networks technologies feature several benefits including higher spectral efficiency, system capacity and therefore have been widely viewed as the promising paradigm for next-generation optical transport networks. Dedicated path protection for elastic optical networks has been of ever-increasing importance in the era of information society thanks to its near-immediate recovery speed and remarkably simple operations in guaranteeing the connectivity of information flows. Inspired by the observation that the today premium network traffic traveling in fiber links accounts for roughly 25% of total traffic and the best-effort traffic constitutes the remaining, we propose a ne...