… multicarrier (MC) system operating on fading channels, where both modulation and
demodulation blocks are modeled by deep neural networks (… by deep learning (DL) in this work. …

… of deep learning schemes have endeavoured to integrate deep neural networks (DNNs) into
channel coded systems … and conceive a turbo-style multi-carrier auto-encoder (MC-AE) for …

… deep learning (DL) based ASR, where it has been shown that simple convolutional neural
networks (… With the advent of spectrally efficient filtered multicarrier waveforms, we propose in …

… algorithm for phase noise compensation in multicarrier systems. The major advantages of it
… We consider OFDM and GFDM systems as representative multicarrier systems. For channel …

… power of the system while … deep learning-based approach to determine an approximated
optimal solution. Specifically, we employ a typical class of deep learning model, namely, deep …

… • To optimize the implementation structure and complexity of the TSIM-UFMC system, we
propose a deep learningaided signal detector termed as TSIMNet, which covers …

… In this paper, we introduce a deep learning (DL) approach for … systems. In particular, we
consider a massive MIMO Orthogonal Frequency Division Multiplexing (MIMOOFDM) system and …

… (Q) imbalance in multicarrier MIMO full-duplex wireless systems. We approximate the time-…
To improve its performance, we develop a deep learning (DL) network. The DL network is …

… -based (NC-EA) system, based on the multicarrier SIMO framework, is first proposed… deep
neural networks (DNNs), known as the encoder and decoder of an EA. Unlike existing systems…

… and optimisation on the multi-carrier system. This thesis investigates the deep learning for
the multi-carrier signal reception technique in various multi-carrier systems. Relying on the …