262 citations · 867 across the 19 of their papers we have counts for
23 papers
Adaptive Learned Belief Propagation for Decoding Error-Correcting Codes
Alireza Tasdighi, Mansoor Yousefi
Weighted belief propagation (WBP) for the decoding of linear block codes is considered. In WBP, the Tanner graph of the code is unrolled with respect to the iterations of the belie…
Developing an Artificial Intelligence Tool for Personalized Breast Cancer Treatment Plans based on the NCCN Guidelines
Abdul M. Mohammed, Iqtidar Mansoor, Sarah Blythe +1
Cancer treatments require personalized approaches based on a patient's clinical condition, medical history, and evidence-based guidelines. The National Comprehensive Cancer Network…
Quantization of Neural Network Equalizers in Optical Fiber Transmission Experiments
Jamal Darweesh, Nelson Costa, Antonio Napoli +3
The quantization of neural networks for the mitigation of the nonlinear and components' distortions in dual-polarization optical fiber transmission is studied. Two low-complexity n…
Equalization in Dispersion-Managed Systems Using Learned Digital Back-Propagation
Mohannad Abu-Romoh, Nelson Costa, Yves Jaouën +4
In this paper, we investigate the use of the learned digital back-propagation (LDBP) for equalizing dual-polarization fiber-optic transmission in dispersion-managed (DM) links. LDB…
Low Complexity Convolutional Neural Networks for Equalization in Optical Fiber Transmission
Mohannad Abu-romoh, Nelson Costa, Antonio Napoli +3
A convolutional neural network is proposed to mitigate fiber transmission effects, achieving a five-fold reduction in trainable parameters compared to alternative equalizers, and 3…
Complexity Reduction over Bi-RNN-Based Nonlinearity Mitigation in Dual-Pol Fiber-Optic Communications via a CRNN-Based Approach
Abtin Shahkarami, Mansoor Yousefi, Yves Jaouen
Bidirectional recurrent neural networks (bi-RNNs), in particular, bidirectional long short term memory (bi-LSTM), bidirectional gated recurrent unit, and convolutional bi-LSTM mode…
Few-bit Quantization of Neural Networks for Nonlinearity Mitigation in a Fiber Transmission Experiment
Jamal Darweesh, Nelson Costa, Antonio Napoli +4
A neural network is quantized for the mitigation of nonlinear and components distortions in a 16-QAM 9x50km dual-polarization fiber transmission experiment. Post-training additive…
Learned Digital Back-Propagation for Dual-Polarization Dispersion Managed Systems
Mohannad Abu-romoh, Nelson Costa, Antonio Napoli +3
Digital back-propagation (DBP) and learned DBP (LDBP) are proposed for nonlinearity mitigation in WDM dual-polarization dispersion-managed systems. LDBP achieves Q-factor improveme…
Approximating Probability Distributions by ReLU Networks
Manuj Mukherjee, Aslan Tchamkerten, Mansoor Yousefi
How many neurons are needed to approximate a target probability distribution using a neural network with a given input distribution and approximation error? This paper examines thi…
Lower Bound on the Capacity of the Continuous-Space SSFM Model of Optical Fiber
Milad Sefidgaran, Mansoor Yousefi
The capacity of a discrete-time model of optical fiber described by the split-step Fourier method (SSFM) as a function of the signal-to-noise ratio and the number of s…
Bounds on the Approximation Power of Feedforward Neural Networks
Mohammad Mehrabi, Aslan Tchamkerten, Mansoor I. Yousefi
The approximation power of general feedforward neural networks with piecewise linear activation functions is investigated. First, lower bounds on the size of a network are establis…
Polarization-Division Multiplexing Based on the Nonlinear Fourier Transform
Jan-Willem Goossens, Mansoor I. Yousefi, Yves Jaouën +1
Polarization-division multiplexed (PDM) transmission based on the nonlinear Fourier transform (NFT) is proposed for optical fiber communication. The NFT algorithms are generalized…
Capacity-Achieving Input Distribution in Per-Sample Zero-Dispersion Model of Optical Fiber
Jihad Fahs, Aslan Tchamkerten, Mansoor I. Yousefi
The per-sample zero-dispersion channel model of the optical fiber is considered. It is shown that capacity is uniquely achieved by an input probability distribution that has contin…
Nonlinear Frequency-Division Multiplexing in the Focusing Regime
Xianhe Yangzhang, Mansoor I. Yousefi, Alex Alvarado +2
Achievable rates of the nonlinear frequency-division multiplexing (NFDM) and wavelength-division multiplexing (WDM) subject to the same power and bandwidth constraints are computed…
The Asymptotic Capacity of the Optical Fiber
Mansoor I. Yousefi
It is shown that signal energy is the only available degree-of-freedom (DOF) for fiber-optic transmission as the input power tends to infinity. With signal DOFs at the input, $…
Linear and Nonlinear Frequency-Division Multiplexing
Mansoor I. Yousefi, Xianhe Yangzhang
Two signal multiplexing schemes for optical fiber communication are considered: Wavelength-division multiplexing (WDM) and nonlinear frequency-division multiplexing (NFDM), based o…
Upper Bound on the Capacity of a Cascade of Nonlinear and Noisy Channels
Gerhard Kramer, Mansoor I. Yousefi, Frank R. Kschischang
An upper bound on the capacity of a cascade of nonlinear and noisy channels is presented. The cascade mimics the split-step Fourier method for computing waveform propagation govern…
Upper Bound on the Capacity of the Nonlinear Schrödinger Channel
Mansoor I. Yousefi, Gerhard Kramer, Frank R. Kschischang
It is shown that the capacity of the channel modeled by (a discretized version of) the stochastic nonlinear Schrödinger (NLS) equation is upper-bounded by with…
The Kolmogorov-Zakharov Model for Optical Fiber Communication
Mansoor I. Yousefi
A mathematical framework is presented to study the evolution of multi-point cumulants in nonlinear dispersive partial differential equations with random input data, based on the th…
On the Per-Sample Capacity of Nondispersive Optical Fibers
Mansoor I. Yousefi, Frank R. Kschischang
The capacity of the channel defined by the stochastic nonlinear Schrödinger equation, which includes the effects of the Kerr nonlinearity and amplified spontaneous emission noise,…
Information Transmission using the Nonlinear Fourier Transform, Part III: Spectrum Modulation
Mansoor I. Yousefi, Frank R. Kschischang
Motivated by the looming "capacity crunch" in fiber-optic networks, information transmission over such systems is revisited. Among numerous distortions, inter-channel interference…
Information Transmission using the Nonlinear Fourier Transform, Part II: Numerical Methods
Mansoor I. Yousefi, Frank R. Kschischang
In this paper, numerical methods are suggested to compute the discrete and the continuous spectrum of a signal with respect to the Zakharov-Shabat system, a Lax operator underlying…
Information Transmission using the Nonlinear Fourier Transform, Part I: Mathematical Tools
Mansoor I. Yousefi, Frank R. Kschischang
The nonlinear Fourier transform (NFT), a powerful tool in soliton theory and exactly solvable models, is a method for solving integrable partial differential equations governing wa…