2 citations · 3 across the 6 of their papers we have counts for
6 papers
Interference Detection in Spectrum-Blind Multi-User Optical Spectrum as a Service
Agastya Raj, Daniel C. Kilper, Marco Ruffini
With the growing demand for high-bandwidth, low-latency applications, Optical Spectrum as a Service (OSaaS) is of interest for flexible bandwidth allocation within Elastic Optical…
Transfer Learning for EDFA Gain Modeling: A Semi-Supervised Approach Using Internal Amplifier Features
Agastya Raj, Dan Kilper, Marco Ruffini
The gain spectrum of an Erbium-Doped Fiber Amplifier (EDFA) has a complex dependence on channel loading, pump power, and operating mode, making accurate modeling difficult to achie…
Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks
Agastya Raj, Zehao Wang, Frank Slyne +3
We introduce a ML-based architecture for network operators to detect impairments from specific OSaaS users while blind to the users' internal spectrum details. Experimental studies…
Multi-Span Optical Power Spectrum Evolution Modeling using ML-based Multi-Decoder Attention Framework
Agastya Raj, Zehao Wang, Frank Slyne +3
We implement a ML-based attention framework with component-specific decoders, improving optical power spectrum prediction in multi-span networks. By reducing the need for in-depth…
A Robust ADMM-Based Optimization Algorithm For Underwater Acoustic Channel Estimation
Tian Tian, Agastya Raj, Bruno Missi Xavier +3
Accurate estimation of the Underwater acoustic (UWA) is a key part of underwater communications, especially for coherent systems. The severe multipath effects and large delay sprea…
Self-Normalizing Neural Network, Enabling One Shot Transfer Learning for Modeling EDFA Wavelength Dependent Gain
Agastya Raj, Zehao Wang, Frank Slyne +3
We present a novel ML framework for modeling the wavelength-dependent gain of multiple EDFAs, based on semi-supervised, self-normalizing neural networks, enabling one-shot transfer…