Related papers: Experimental Study of Deep Neural Network Equalize…

Terahertz (THz) communication is envisioned as a key technology for 6G and beyond wireless systems owing to its multi-GHz bandwidth. To maintain the same aperture area and the same link budget as the lower frequencies, ultra-massive…

This paper introduces a $H_\infty$-like methodology of coherent filtering for equalization of passive linear quantum systems to help mitigate degrading effects of quantum communication channels. For such systems, which include a wide range…

Optical interconnects are becoming a major bottleneck in scaling up future GPU racks and network switches within data centers. Although 200 Gb/s optical transceivers using PAM-4 modulation have been demonstrated, achieving higher data rates…

Integrating quantum key distribution (QKD) with classical data transmission over the same fiber is crucial for scalable quantum-secured communication. However, noise from classical channels limits QKD distance. We demonstrate the…

We investigate the complexity and performance of recurrent neural network (RNN) models as post-processing units for the compensation of fibre nonlinearities in digital coherent systems carrying polarization multiplexed 16-QAM and 32-QAM…

Optical Diffraction Neural Networks (DNNs), a subset of Optical Neural Networks (ONNs), show promise in mirroring the prowess of electronic networks. This study introduces the Hybrid Diffraction Neural Network (HDNN), a novel architecture…

Convolutional neural networks are paramount in image and signal processing including the relevant classification and training tasks alike and constitute for the majority of machine learning compute demand today. With convolution operations…

This paper studies the impact of probabilistic shaping on effective signal-to-noise ratios (SNRs) and achievable information rates (AIRs) in a back-to-back configuration and in unrepeated nonlinear fiber transmissions. For back-to-back,…

In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a…

Asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) is theoretically more power efficient but less spectrally efficient than DC-bias OFDM (DCO-OFDM), with less power allocating to the informationless bias…

It is known that phase noise (PN) can cause link performance to degrade severely in orthogonal frequency division multiplexing (OFDM) systems, such as IEEE 802.11, 3GPP LTE and 5G. As opposed to prior PN mitigation schemes that assume…

Digital predistortion (DPD) is essential for mitigating nonlinearity in RF power amplifiers, particularly for wideband applications. This paper presents TCN-DPD, a parameter-efficient architecture based on temporal convolutional networks,…

In this paper, we study the equalization design for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with insufficient cyclic prefix (CP). In particular, the signal detection performance is…

Quantum key distribution (QKD), the distribution of quantum secured keys useful for data encryption, is expected to have a crucial impact in the next decades. However, although the notable achievements accomplished in the last twenty years,…

In this paper, it is identified that lowering the reference level at the vector signal analyzer can significantly improve the performance of iterative learning control (ILC). We present a mathematical explanation for this phenomenon, where…

To satisfy the growing throughput demand of data-intensive applications, the performance of optical communication systems increased dramatically in recent years. With higher throughput, more advanced equalizers are crucial, to compensate…

Compared with electrical neural networks, optical neural networks (ONNs) have the potentials to break the limit of the bandwidth and reduce the consumption of energy, and therefore draw much attention in recent years. By far, several types…

We experimentally demonstrate the enhanced atmospheric turbulence resiliency in a 137.8 Gbit/s/mode mode-division multiplexing free-space optical communication link through the application of a successive interference cancellation digital…

Multi-channel speech enhancement seeks to utilize spatial information to distinguish target speech from interfering signals. While deep learning approaches like the dual-path convolutional recurrent network (DPCRN) have made strides,…

Transformers process tokens in parallel but are temporally shallow: at position $t$, each layer attends to key-value pairs computed based on the previous layer, yielding a depth capped by the number of layers. Recurrent models offer…