Search Results for author: Kumar Vijay Mishra

Found 38 papers, 1 papers with code

Circularly Polarized Fabry-Perot Cavity Sensing Antenna Design using Generative Model

no code implementations29 Sep 2022 Kainat Yasmeen, Kumar Vijay Mishra, A. V. Subramanyam, Shobha Sundar Ram

We consider the problem of designing a circularly polarized Fabry-P'erot cavity (FPC) antenna for S-band sensing applications.

SOLBP: Second-Order Loopy Belief Propagation for Inference in Uncertain Bayesian Networks

no code implementations16 Aug 2022 Conrad D. Hougen, Lance M. Kaplan, Magdalena Ivanovska, Federico Cerutti, Kumar Vijay Mishra, Alfred O. Hero III

In second-order uncertain Bayesian networks, the conditional probabilities are only known within distributions, i. e., probabilities over probabilities.

Inverse Extended Kalman Filter -- Part II: Highly Non-Linear and Uncertain Systems

no code implementations13 Aug 2022 Himali Singh, Arpan Chattopadhyay, Kumar Vijay Mishra

The purpose of this paper and the companion paper (Part I) is to address the inverse filtering problem in non-linear systems by proposing an inverse extended Kalman filter (I-EKF).

Terahertz-Band Integrated Sensing and Communications: Challenges and Opportunities

no code implementations2 Aug 2022 Ahmet M. Elbir, Kumar Vijay Mishra, Symeon Chatzinotas, Mehdi Bennis

The sixth generation (6G) wireless networks aim to achieve ultra-high data transmission rates, very low latency and enhanced energy-efficiency.

Federated Learning for THz Channel Estimation

no code implementations13 Jul 2022 Ahmet M. Elbir, Wei Shi, Kumar Vijay Mishra, Symeon Chatzinotas

This paper addresses two major challenges in terahertz (THz) channel estimation: the beam-split phenomenon, i. e., beam misalignment because of frequency-independent analog beamformers, and computational complexity because of the usage of ultra-massive number of antennas to compensate propagation losses.

Federated Learning

Implicit Channel Learning for Machine Learning Applications in 6G Wireless Networks

no code implementations24 Jun 2022 Ahmet M. Elbir, Wei Shi, Kumar Vijay Mishra, Anastasios K. Papazafeiropoulos, Symeon Chatzinotas

Without channel estimation, the proposed approach exhibits approximately 60% improvement in image and speech classification tasks for diverse scenarios such as millimeter wave and IEEE 802. 11p vehicular channels.

BIG-bench Machine Learning

An Overview of Advances in Signal Processing Techniques for Classical and Quantum Wideband Synthetic Apertures

no code implementations11 May 2022 Peter Vouras, Kumar Vijay Mishra, Alexandra Artusio-Glimpse, Samuel Pinilla, Angeliki Xenaki, David W. Griffith, Karen Egiazarian

Rapid developments in synthetic aperture (SA) systems, which generate a larger aperture with greater angular resolution than is inherently possible from the physical dimensions of a single sensor alone, are leading to novel research avenues in several signal processing applications.

Federated Channel Learning for Intelligent Reflecting Surfaces With Fewer Pilot Signals

no code implementations6 May 2022 Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

Channel estimation is a critical task in intelligent reflecting surface (IRS)-assisted wireless systems due to the uncertainties imposed by environment dynamics and rapid changes in the IRS configuration.

Federated Learning

The Rise of Intelligent Reflecting Surfaces in Integrated Sensing and Communications Paradigms

no code implementations14 Apr 2022 Ahmet M. Elbir, Kumar Vijay Mishra, M. R. Bhavani Shankar, Symeon Chatzinotas

The intelligent reflecting surface (IRS) alters the behavior of wireless media and, consequently, has potential to improve the performance and reliability of wireless systems such as communications and radar remote sensing.

Unfolding-Aided Bootstrapped Phase Retrieval in Optical Imaging

no code implementations3 Mar 2022 Samuel Pinilla, Kumar Vijay Mishra, Igor Shevkunov, Mojtaba Soltanalian, Vladimir Katkovnik, Karen Egiazarian

Phase retrieval in optical imaging refers to the recovery of a complex signal from phaseless data acquired in the form of its diffraction patterns.

Phase Retrieval for Radar Waveform Design

no code implementations27 Jan 2022 Samuel Pinilla, Kumar Vijay Mishra, Brian M. Sadler, Henry Arguello

The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform.

Radar waveform design

Co-Pulsing FDA Radar

no code implementations18 Jan 2022 Wanghan Lv, Kumar Vijay Mishra, Shichao Chen

By exploiting these DoFs, we develop C-Cube auto-pairing (CCing) algorithm, in which all the parameters are ipso facto paired during a joint estimation.

Joint Transmit and Reflective Beamformer Design for Secure Estimation in IRS-Aided WSNs

no code implementations12 Jan 2022 Mohammad Faisal Ahmed, Kunwar Pritiraj Rajput, Naveen K. D. Venkategowda, Kumar Vijay Mishra, Aditya K. Jagannatham

Wireless sensor networks (WSNs) are vulnerable to eavesdropping as the sensor nodes (SNs) communicate over an open radio channel.

Inverse Extended Kalman Filter -- Part I: Fundamentals

no code implementations5 Jan 2022 Himali Singh, Arpan Chattopadhyay, Kumar Vijay Mishra

The purpose of this paper and the companion paper (Part II) is to develop the theory of I-EKF in detail.

Unique Bispectrum Inversion for Signals with Finite Spectral/Temporal Support

no code implementations11 Nov 2021 Samuel Pinilla, Kumar Vijay Mishra, Brian M. Sadler

In this paper, we present a an approach that uniquely recovers signals with finite spectral support (band-limited signals) from at least $3B$ measurements of its bispectrum function (BF), where $B$ is the signal's bandwidth.

Joint Radar-Communications Processing from a Dual-Blind Deconvolution Perspective

no code implementations11 Nov 2021 Edwin Vargas, Kumar Vijay Mishra, Roman Jacome, Brian M. Sadler, Henry Arguello

When the radar receiver is not collocated with the transmitter, such as in passive or multistatic radars, the transmitted signal is also unknown apart from the target parameters.

IRS-Aided Radar: Enhanced Target Parameter Estimation via Intelligent Reflecting Surfaces

no code implementations25 Oct 2021 Zahra Esmaeilbeig, Kumar Vijay Mishra, Mojtaba Soltanalian

We demonstrate that the IRS can provide a virtual or non-line-of-sight (NLOS) link between the radar and target leading to an enhanced radar performance.

Resource Allocation in Heterogeneously-Distributed Joint Radar-Communications under Asynchronous Bayesian Tracking Framework

no code implementations23 Aug 2021 Linlong Wu, Kumar Vijay Mishra, Bhavani Shankar M. R., Björn Ottersten

Optimal allocation of shared resources is key to deliver the promise of jointly operating radar and communications systems.

Heterogeneously-Distributed Joint Radar Communications: Bayesian Resource Allocation

no code implementations29 Jul 2021 Linlong Wu, Kumar Vijay Mishra, Bhavani Shankar M. R., Björn Ottersten

In this paper, we focus on a heterogeneous radar and communication network (HRCN), which consists of various generic radars for multiple target tracking (MTT) and wireless communications for multiple users.

Joint Radar-Communication

Information Geometry and Classical Cramér-Rao Type Inequalities

no code implementations2 Apr 2021 Kumar Vijay Mishra, M. Ashok Kumar

We examine the role of information geometry in the context of classical Cram\'er-Rao (CR) type inequalities.

Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming

no code implementations27 Feb 2021 Ahmet M. Elbir, Kumar Vijay Mishra, Symeon Chatzinotas

Wireless communications and sensing at terahertz (THz) band are increasingly investigated as promising short-range technologies because of the availability of high operational bandwidth at THz.

Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems

no code implementations15 Feb 2021 Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

Then, we leverage federated learning (FL) with dropout learning (DL) to train a learning model on the local dataset of users, who estimate the beamformers by feeding the model with their channel data.

Federated Learning

Non-Contact Vital Signs Detection with UAV-Borne Radars

no code implementations27 Nov 2020 Yu Rong, Richard M. Gutierrez, Kumar Vijay Mishra, Daniel W. Bliss

Aggregating radar measurements with the information from other sensors is broadening the applications of drones in life-critical situations.

Disaster Response

Hybrid Federated and Centralized Learning

no code implementations13 Nov 2020 Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

We address this through a novel hybrid federated and centralized learning (HFCL) framework to effectively train a learning model by exploiting the computational capability of the clients.

Federated Learning

Cognitive Learning-Aided Multi-Antenna Communications

no code implementations7 Oct 2020 Ahmet M. Elbir, Kumar Vijay Mishra

We discuss DL design challenges from the perspective of data, learning, and transceiver architectures.

Federated Learning online learning +1

Displaced Sensor Automotive Radar Imaging

no code implementations6 Oct 2020 Guohua Wang, Kumar Vijay Mishra

Contrary to these works, we develop a displaced multiple-input multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radar signal model under coarse synchronization with only frame-level alignment.

A Survey of Deep Learning Architectures for Intelligent Reflecting Surfaces

no code implementations5 Sep 2020 Ahmet M. Elbir, Kumar Vijay Mishra

Data-driven techniques, such as deep learning (DL), are critical in addressing these challenges.

Localization with One-Bit Passive Radars in Narrowband Internet-of-Things using Multivariate Polynomial Optimization

no code implementations29 Jul 2020 Saeid Sedighi, Kumar Vijay Mishra, M. R. Bhavani Shankar, Björn Ottersten

To support the low-capacity links to the fusion center (FC), the range estimates obtained at individual sensors are then converted to one-bit data.

Co-Designing Statistical MIMO Radar and In-band Full-Duplex Multi-User MIMO Communications

no code implementations26 Jun 2020 Jiawei Liu, Kumar Vijay Mishra, Mohammad Saquib

We consider a spectral sharing problem in which a statistical (or widely distributed) multiple-input-multiple-output (MIMO) radar and an in-band full-duplex (IBFD) multi-user MIMO (MU-MIMO) communications system concurrently operate within the same frequency band.

Sparse Array Selection Across Arbitrary Sensor Geometries with Deep Transfer Learning

no code implementations24 Apr 2020 Ahmet M. Elbir, Kumar Vijay Mishra

Sparse sensor array selection arises in many engineering applications, where it is imperative to obtain maximum spatial resolution from a limited number of array elements.

Direction of Arrival Estimation Transfer Learning

Generalized Bayesian Cramér-Rao Inequality via Information Geometry of Relative $α$-Entropy

no code implementations11 Feb 2020 Kumar Vijay Mishra, M. Ashok Kumar

The relative $\alpha$-entropy is the R\'enyi analog of relative entropy and arises prominently in information-theoretic problems.


Cramér-Rao Lower Bounds Arising from Generalized Csiszár Divergences

no code implementations14 Jan 2020 M. Ashok Kumar, Kumar Vijay Mishra

We study the geometry of probability distributions with respect to a generalized family of Csisz\'ar $f$-divergences.

A Family of Deep Learning Architectures for Channel Estimation and Hybrid Beamforming in Multi-Carrier mm-Wave Massive MIMO

1 code implementation20 Dec 2019 Ahmet M. Elbir, Kumar Vijay Mishra, M. R. Bhavani Shankar, Björn Ottersten

Hybrid analog and digital beamforming transceivers are instrumental in addressing the challenge of expensive hardware and high training overheads in the next generation millimeter-wave (mm-Wave) massive MIMO (multiple-input multiple-output) systems.

Low-Complexity Limited-Feedback Deep Hybrid Beamforming for Broadband Massive MIMO Communications

no code implementations31 Oct 2019 Ahmet M. Elbir, Kumar Vijay Mishra

In broadband millimeter-wave (mm-Wave) systems, it is desirable to design hybrid beamformers with common analog beamformer for the entire band while employing different baseband beamformers in different frequency sub-bands.

Signal Processing

Doppler-Resilient 802.11ad-Based Ultra-Short Range Automotive Joint Radar-Communications System

no code implementations4 Feb 2019 Gaurav Duggal, Shelly Vishwakarma, Kumar Vijay Mishra, Shobha Sundar Ram

We present an ultra-short range IEEE 802. 11ad-based automotive joint radar-communications (JRC) framework, wherein we improve the radar's Doppler resilience by incorporating Prouhet-Thue-Morse sequences in the preamble.

Dictionary Learning for Adaptive GPR Landmine Classification

no code implementations24 May 2018 Fabio Giovanneschi, Kumar Vijay Mishra, Maria Antonia Gonzalez-Huici, Yonina C. Eldar, Joachim H. G. Ender

For the case of abandoned anti-personnel landmines classification, we compare the performance of K-SVD with three online algorithms: classical Online Dictionary Learning, its correlation-based variant, and DOMINODL.

Classification Dictionary Learning +3

Cognitive Radar Antenna Selection via Deep Learning

no code implementations27 Feb 2018 Ahmet M. Elbir, Kumar Vijay Mishra, Yonina C. Eldar

Direction of arrival (DoA) estimation of targets improves with the number of elements employed by a phased array radar antenna.

General Classification Multi-class Classification

Precise Semidefinite Programming Formulation of Atomic Norm Minimization for Recovering d-Dimensional ($d\geq 2$) Off-the-Grid Frequencies

no code implementations2 Dec 2013 Weiyu Xu, Jian-Feng Cai, Kumar Vijay Mishra, Myung Cho, Anton Kruger

Recent research in off-the-grid compressed sensing (CS) has demonstrated that, under certain conditions, one can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous.

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