3 citations · 6 across the 15 of their papers we have counts for
16 papers
Radio-Optical Confluence in Intelligent Edge Networks
Akshita Gupta, Devika Dass, Agastya Raj +4
Challenges associated with densification of radio access networks are motivating exploration of more efficient and scalable architectures. We examine recent progress in one directi…
OSNR/GSNR Prediction in Brownfield Links via a DLM-Anchored Hybrid Physics/ML Model
Agastya Raj, Venkata Virajit Garbhapu, Hiroyuki Ishihara +5
We present a DLM-anchored hybrid physics/ML framework for brownfield optical links that accurately predicts per-channel power, OSNR, and GSNR. Calibrating span/ILA boundaries via D…
Fully Unsupervised Detection of Physical Contacts on Subsea Cables via State-of-Polarization Monitoring
Agastya Raj, Alvaro Doval, Tian Tian +2
We present a fully unsupervised Fast-Slow DSVDD detector for continuous State-of-Polarization monitoring on a deployed subsea cable. Trained without event labels, it ranks all five…
DAS-AIS Association Patterns for Vessel Monitoring on an Operational Subsea Fibre Link
Tian Tian, Agastya Raj, Lara Flanagan +4
We present a case study on the Emerald Fibre Bridge Link, an operational subsea telecom cable connecting Dublin and North Wales, examining DAS vessel-related signatures jointly wit…
Sea-Scan: High-Accuracy, ML-based Dark Vessel Detection and Localisation via Weakly Supervised DAS Monitoring
Tian Tian, Agastya Raj, Lara Flanagan +2
We present an ML-based vessel detection and localization system, trained with weak supervision from imperfect AIS labels, that achieves a 97.8% detection rate at 1.98% false-trigge…
Deep Learning Based Multi-Step Channel Prediction for Adaptive Underwater Acoustic OFDM Systems
Tian Tian, Ying Zhang, Agastya Raj +2
We develop an adaptive OFDM framework for underwater acoustic communications based on PatchCSI-T, a Transformer-based multistep channel prediction model with feature-independent mo…
Spectrum Configuration Framework for Throughput Maximization in Open Systems with Roll-Off-Based QoT Optimization
Peyman Pahlevanzadeh, Venkata Virajit Garbhapu, Agastya Raj +3
We propose a spectrum-configuration framework for open and disaggregated optical systems that maximizes throughput while guaranteeing the quality of transmission (QoT) margins. The…
Generalized few-shot transfer learning architecture for modeling the EDFA gain spectrum
Agastya Raj, Zehao Wang, Tingjun Chen +2
Accurate modeling of the gain spectrum in Erbium-Doped Fiber Amplifiers (EDFAs) is essential for optimizing optical network performance, particularly as networks evolve toward mult…
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…
Coexistence of Digital Coherent, mmWave and sub-THz Analog RoF Services using OSaaS over converged access-metro live production network
Devika Dass, Amol Delmade, Agastya Raj +4
We demonstrate the end-to-end transmission of digital coherent and analog radio-over-fiber signals, at mmWave and sub-THz frequencies, over the HEAnet live production metro network…
Real-Time Streaming Telemetry Based Detection and Mitigation of OOK and Power Interference in Multi-User OSaaS Networks
Agastya Raj, Devika Dass, Daniel C. Kilper +1
We present a framework to identify and mitigate rogue OOK signals and user-generated power interference in a multi-user Optical-Spectrum-as-a-Service network. Experimental tests on…
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…