106 citations · 310 across the 82 of their papers we have counts for
90 papers
Distribution of -th Maximum Order Statistics of Independent, & Non-Identical SNR random variables in fading and its applications in
Srinivas Sagar, Athira Subhash, Sheetal Kalyani
This paper employs extreme value theory to establish the asymptotic distribution of the -th maximum order statistics of signal to noise ratio (SNR) for a fading channel wi…
Breaking the Script Barrier: Enabling Automatic Alignment for PoS-based ASR Error Analysis in Non-Latin Scripts
Prasenjit K Mudi, Dahlia Devapriya, Sheetal Kalyani
Automatic Speech Recognition (ASR) systems are commonly evaluated using aggregate metrics such as Word Error Rate (WER), which do not capture the linguistic structure of errors. Fi…
Neural Equalisers for Highly Compressed Faster-than-Nyquist Signalling: Design, Performance, Complexity and Robustness
Shubham Paul, Sheetal Kalyani, Nambi Sheshadri +1
Faster-than-Nyquist (FTN) signalling has emerged as a compelling technique for enhancing spectral efficiency in bandwidth-constrained communication systems. By intentionally introd…
Maximizing Qubit Throughput under Buffer Decoherence and Variability in Generation
Padma Priyanka, Avhishek Chatterjee, Sheetal Kalyani
Quantum communication networks require transmission of high-fidelity, uncoded qubits for applications such as entanglement distribution and quantum key distribution. However, curre…
Federated Learning of Binary Neural Networks: Enabling Low-Cost Inference
Nitin Priyadarshini Shankar, Soham Lahiri, Sheetal Kalyani +1
Federated Learning (FL) preserves privacy by distributing training across devices. However, using DNNs is computationally intensive at the low-powered edge during inference. Edge d…
Tuning-Free Structured Sparse Recovery of Multiple Measurement Vectors using Implicit Regularization
Lakshmi Jayalal, Sheetal Kalyani
Recovering jointly sparse signals in the multiple measurement vectors (MMV) setting is a fundamental problem in machine learning, but traditional methods often require careful para…
Integrating OTFS in Airplane-Aided Next-Generation Networking
Ashok S Kumar, Shashank Shekhar, Gokularam Muthukrishnan +2
Next-generation networks explore the opportunistic assistance of airliner/high-altitude platforms (HAPs) in delivering high data rates for terrestrial networks to ensure consistent…
RIS, Active RIS or RDARS: A Comparative Insight Through the Lens of Energy Efficiency
Aparna V C, Shashank Shekhar, Sheetal Kalyani
Multiplicative fading is a major limitation of reconfigurable intelligent surfaces (RIS), restricting their effective coverage in both existing sub-6GHz systems and future mmWave n…
BERTO: Intent-Driven Network Time Series Forecasting via Natural Language Operator Preferences
Nitin Priyadarshini Shankar, Vaibhav Singh, Sheetal Kalyani +1
Traditional cellular traffic forecasting models are optimized for minimizing symmetric errors, leaving them indifferent to shifting operational priorities. To bridge this gap, we i…
Structured Sparsity and Weight-adaptive Pruning for Memory and Compute efficient Whisper models
Prasenjit K Mudi, Anshi Sachan, Dahlia Devapriya +1
Whisper models have achieved remarkable progress in speech recognition; yet their large size remains a bottleneck for deployment on resource-constrained edge devices. This paper pr…
The Rendezvous Between Extreme Value Theory and Next-generation Networks
Srinivas Sagar, Athira Subhash, Chen-Feng Liu +6
Promising technologies such as massive multiple-input and multiple-output, reconfigurable intelligent reflecting surfaces, non-terrestrial networks, millimetre wave communication,…
Online waveform selection for cognitive radar
Thulasi Tholeti, Avinash Rangarajan, Sheetal Kalyani
Designing a cognitive radar system capable of adapting its parameters is challenging, particularly when tasked with tracking a ballistic missile throughout its entire flight. In th…
Textless NLP -- Zero Resource Challenge with Low Resource Compute
Krithiga Ramadass, Abrit Pal Singh, Srihari J +1
This work addresses the persistent challenges of substantial training time and GPU resource requirements even when training lightweight encoder-vocoder models for Textless NLP. We…
Golden Ratio Search: A Low-Power Adversarial Attack for Deep Learning based Modulation Classification
Deepsayan Sadhukhan, Nitin Priyadarshini Shankar, Sheetal Kalyani
We propose a minimal power white box adversarial attack for Deep Learning based Automatic Modulation Classification (AMC). The proposed attack uses the Golden Ratio Search (GRS) me…
Learning Rate Optimization for Deep Neural Networks Using Lipschitz Bandits
Padma Priyanka, Sheetal Kalyani, Avhishek Chatterjee
Learning rate is a crucial parameter in training of neural networks. A properly tuned learning rate leads to faster training and higher test accuracy. In this paper, we propose a L…
Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RIS
Dahlia Devapriya, Aparna V C, Sheetal Kalyani
In reconfigurable intelligent surface (RIS) aided systems, the joint optimization of the precoder matrix at the base station and the phase shifts of the RIS elements involves signi…
Tuning-Free Online Robust Principal Component Analysis through Implicit Regularization
Lakshmi Jayalal, Gokularam Muthukrishnan, Sheetal Kalyani
The performance of the standard Online Robust Principal Component Analysis (OR-PCA) technique depends on the optimum tuning of the explicit regularizers and this tuning is dataset…
Source Enumeration using the Distribution of Angles: A Robust and Parameter-Free Approach
Gokularam Muthukrishnan, Siva Shanmugam, Sheetal Kalyani
Source enumeration, the task of estimating the number of sources from the signal received by the array of antennas, is a critical problem in array signal processing. Numerous metho…
First line of defense: A robust first layer mitigates adversarial attacks
Janani Suresh, Nancy Nayak, Sheetal Kalyani
Adversarial training (AT) incurs significant computational overhead, leading to growing interest in designing inherently robust architectures. We demonstrate that a carefully desig…
Product and Ratio of Two Shadowed Random Variables and its Application to Wireless Communication
Shashank Shekhar, Sheetal Kalyani
This work studies the product and ratio statistics of independent and non-identically distributed (i.n.i.d) shadowed random variables. We derive the series expression for…
Randomness Helps Rigor: A Probabilistic Learning Rate Scheduler Bridging Theory and Deep Learning Practice
Dahlia Devapriya, Thulasi Tholeti, Janani Suresh +1
Learning rate schedulers have shown great success in speeding up the convergence of learning algorithms in practice. However, their convergence to a minimum has not been proven the…
DRL-AdaPart: DRL-Driven Adaptive STAR-RIS Partitioning for Fair and Efficient Resource Utilization
Ashok S. Kumar, Nancy Nayak, Sheetal Kalyani +2
Efficient resource utilization is proposed for simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) to ensure fair and high data rates. We opti…
Multi-RIS Communication Systems: Asymptotic analysis of best RIS selection for i.n.i.d. Random Variables using Extreme Value Theory
Srinivas Sagar, Sheetal Kalyani
This paper investigates the performance of multiple reconfigurable intelligent surfaces (multi-RIS) communication systems where the RIS link with the highest signal-to-noise-ratio…
Practical Radar Sensing Using Two Stage Neural Network for Denoising OTFS Signals
Ashok S Kumar, Sheetal Kalyani
Our objective is to derive the range and velocity of multiple targets from the delay-Doppler domain for radar sensing using orthogonal time frequency space (OTFS) signaling. Noise…