Jitendra Tugnait

Auburn University | AU · Department of Electrical & Computer Engineering

We consider the problem of inferring the conditional independence graph (CIG) of a high-dimensional stationary multivariate Gaussian time series. A sparse-group lasso based frequency-domain formulation of the problem has been considered in the literature where the objective is to estimate the sparse inverse power spectral density (PSD) of the data....

We consider the problem of inferring the conditional independence graph (CIG) of a high-dimensional stationary multivariate Gaussian time series. In a time series graph, each component of the vector series is represented by distinct node, and associations between components are represented by edges between the corresponding nodes. We formulate the...

We consider the problem of inferring the conditional independence graph (CIG) of a sparse, high-dimensional stationary multivariate Gaussian time series. A sparse-group lasso-based frequency-domain formulation of the problem based on frequency-domain sufficient statistic for the observed time series is presented. We investigate an alternating direc...

We consider the problem of inferring the conditional independence graph (CIG) of a sparse, high-dimensional stationary multivariate Gaussian time series. A sparse-group lasso-based frequency-domain formulation of the problem based on frequency-domain sufficient statistic for the observed time series is presented. We investigate an alternating direc...

We consider the problem of learning a sparse undirected graph underlying a given set of multivariate data. We focus on graph Laplacian-related constraints on the sparse precision matrix that encodes conditional dependence between the random variables associated with the graph nodes. Under these constraints the off-diagonal elements of the precision...

We consider the problem of learning a sparse undirected graph underlying a given set of multivariate data. We focus on graph Laplacian-related constraints on the sparse precision matrix that encodes conditional dependence between the random variables associated with the graph nodes. Under these constraints the off-diagonal elements of the precision...

We consider the problem of detecting the presence of an improper complex-valued signal, common among two or more sensors (channels), in the presence of spatially independent, colored improper noise and additive outliers. A source of improper noise is in-phase/quadrature-phase imbalance during down-conversion of bandpass noise to baseband at the rec...

In this paper, the problem of effective and robust delivery of Dynamic Adaptive Streaming over HTTP (DASH) videos over an orthogonal frequency-division multiplexing access (OFDMA) network is studied. Motivated by a measurement study, we propose to explore the request interval and robust rate prediction for DASH over OFDMA. We first formulate an off...

We consider the problem of comparing two complex multivariate random signal realizations, possibly contaminated with additive outliers, to ascertain whether they have identical power spectral densities. For clean data (i.e., known to be outlier free), a binary hypothesis testing formulation in frequencydomain, utilizing estimated power spectral den...

As wired/wireless networks become more and more complex, the fundamental assumptions made by many existing TCP variants may not hold true anymore. In this paper, we develop a model-free, smart congestion control algorithm based on deep reinforcement learning (DRL), which has a high potential in dealing with the complex and dynamic network environme...

In a time-division duplex (TDD) multiple antenna system, the channel state information (CSI) can be estimated using reverse training. A pilot spoofing (contamination) attack occurs when during the training phase, an adversary (spoofer) also sends synchronized, identical training (pilot) signal as that of the legitimate receiver. This contaminates c...

In a time-division duplex (TDD) multiple antenna system the channel state information (CSI) can be estimated using reverse training. In multi-cell multi-user massive MIMO systems, pilot contamination degrades CSI estimation performance and adversely affects massive MIMO system performance. In this paper we consider a subspace-based semi-blind appro...

In a time-division duplex (TDD) multiple antenna system, the channel state information (CSI) can be estimated using reverse training. A pilot spoofing attack occurs when during the training phase, an adversary (spoofer) also sends identical training (pilot) signal as that of the legitimate receiver. This contaminates channel estimation and alters t...

In this paper, we investigate the problem of robust congestion control in infrastructure based cognitive radio networks (CRN). We develop an active queue management (AQM) algorithm, termed MAQ, which is based on multiple model predictive control (MMPC). The goal is to stabilize the TCP queue at the base station (BS) under disturbances from the time...

We consider the problem of testing whether a complex-valued vector random sequence is proper, i.e., if the sequence is uncorrelated with its complex conjugate. Previous non-parametric approaches to impropriety testing are limited to a sequence of independent random vectors, typically assumed to be Gaussian. In this work, we extend the results to st...

The problem of multiple antenna spectrum sensing is addressed where the receiver noise is allowed to be temporally colored with unknown power spectral density, but must be spatially uncorrelated. The signal is received over a possibly frequency-selective, unknown channel. A comprehensive overview of spectrum sensing approaches under colored noise i...

We consider detection of spoofing relay attack in time-division duplex (TDD) multiple antenna systems where an adversary operating in a full-duplex mode, amplifies and forwards the training signal of the legitimate receiver. In TDD systems, the channel state information can be acquired using reverse training. The spoofing relay attack contaminates...

This paper considers optimal multiband transmission under hostile jamming, where both the authorized user and the jammer are power-limited and operate against each other. The strategic decision making of the authorized user and the jammer is modeled as a two-party zero-sum game, where the payoff function is the capacity that can be achieved by the...

We study the achievable secure degrees of freedom (DoF) in a cooperative MIMO cognitive radio system comprised of one primary source-destination pair, multiple secondary source-destination pairs and an eavesdropper against whom the primary user intends to secure its data. In this system, multiple secondary user pairs help to secure primary user?s d...

We consider the problem of comparing two complex multivariate random signal realizations to ascertain whether they have identical power spectral densities. Past work on this problem is limited to either scalar signals or real-valued multivariate signals. A binary hypothesis testing approach is formulated and a generalized likelihood ratio test (GLR...

In a time-division duplex (TDD) multiple antenna system, the channel state information (CSI) can be acquired using reverse training. A pilot contamination attack occurs when during the training phase, an adversary also sends identical training (pilot) signal as that of the legitimate receiver. This contaminates the channel estimation phase and can...

We study the secure degrees of freedom (DoF) in a cognitive radio system. A cognitive radio user helps to secure primary user's transmission against an eavesdropper and in return, primary users allows secondary user to access its licensed spectrum. All users are equipped with multiple antennas. We investigate the secure DoF using interference align...

Reverse-time chaos can be used to realise hardware chaotic systems that can operate at speeds equivalent to existing state-of-the-art while requiring significantly less complex circuitry. Unlike traditional chaotic systems, which require significant analogue hardware that is difficult to realise at high speed, the reverse-time system can be realise...

We consider a $K$-user multiple input multiple output (MIMO) Y channel consisting of $K(geq 3)$ users and a relay. Each user has $K - 1$ independent messages for all the other $K - 1$ users. Degrees of freedom (DoF) of such channels is not known in general but it is known that the DoF of $K(K - 1)/2$ is achievable for a network operating in a half-...

We consider a physical layer approach to enhance wireless security by using the unique wireless channel state information (CSI) of a legitimate user to authenticate subsequent transmissions (messages) from this user, thereby denying access to any spoofer whose CSI would significantly differ from that of the legitimate user by virtue of a different...

This paper develops two spectrally efficient orthogonal frequency division multiplexing (OFDM)-based multicarrier transmission schemes: a scheme with message-driven idle subcarriers (MC-MDIS) and another with message-driven strengthened subcarriers (MC-MDSS). The basic idea in MC-MDIS is to carry part of the information, which is named carrier bits...

We consider a recently proposed generalized likelihood ratio test (GLRT) for comparing two complex multivariate random signal realizations to ascertain whether they have identical power spectral densities. In this paper we analyze the performance of this GLRT by deriving an approximate asymptotic distribution of the test statistic under the alterna...

We study weighted energy efficiency maximization for multiple-input multiple-output cognitive multiple access channels under both secondary user transmit power constraint and primary user interference power constraint. Energy efficiency is defined as the ratio of weighted sum rate and energy consumption including both transmission and circuit energ...

We consider a physical layer approach to enhance wireless security by using the unique wireless channel state information (CSI) of a legitimate user to authenticate subsequent transmissions (messages) from this user, thereby denying access to any spoofer whose CSI would significantly differ from that of the legitimate user by virtue of a different...

The problem of multiantenna spectrum sensing is considered where the receiver noise is allowed to be temporally colored with unknown power spectral density (PSD), but must be spatially uncorrelated. The signal is received over a possibly frequency-selective, unknown channel. A generalized likelihood ratio test (GLRT) for multiantenna spectrum sensi...

In this paper, we consider a K-user MIMO (multiple input multiple output) Y channel consisting of K, K ≥3, users and a relay. Each user has K - 1 independent messages for all the other K-1 users. With the deployment of multiple antennas at both end users and the relay, K(K - 1) messages can be conveyed to their desired receivers within two time slo...

We formulate the design of energy efficiency maximization for a single secondary link in an underlay spectrum sharing cognitive radio network under an SU (secondary user) transmit-power constraint and an upperbound on the interference power at the PU (primary user). We propose energy efficient precoding (beamforming) for the SU transmitter to maxim...

Detection of cyclostationary primary user (PU) signals in colored Gaussian noise for cognitive radio systems is considered based on looking for single or multiple cycle frequencies at single or multiple time lags in the cyclic autocorrelation function (CAF) of the noisy PU signal. We explicitly exploit the knowledge that under the null hypothesis o...

In this paper, we design relay precoder in a MIMO cognitive radio network where two-way transmission of multiple secondary user pairs occurs concurrently with primary network's transmission. We propose an interference alignment like precoder design which jointly aligns the direction of interference and the desired signal while interference to prima...

We consider joint optimization of cooperative spectrum sensing, channel access and power allocation in an overlay multiband cognitive radio network. A soft-decision cooperative spectrum sensing concept using continuous-valued sensing test statistics is considered, instead of making hard binary decisions as in traditional hypothesis testing spectrum...

Frequency spectrum and energy are two key resources of green cognitive radio networks with battery-powered wireless terminals. The issues of how to utilize sparse frequency spectrum and limited energy resource pose challenges to the design of sensing and power allocation strategies that affect both throughput and energy consumption. In this paper,...

It has been shown that the performance of communication systems based on low dimensional chaotic systems with exact analytic solutions containing a single fixed basis function may exhibit performance comparable to that of nonchaotic systems. Previously, novel low frequency (LF) oscillators exhibiting solvable, chaotic behavior have been proposed, a...

In this correspondence, a method is presented for estimating double-selective channels using superimposed training (ST). The estimator is based on a subspace projection of the time-varying channel onto a set of two dimensional orthogonal functions. These functions are formed via the outer product of the discrete prolate spheroidal basis vectors and...

We consider the problem of comparing two complex multivariate random signal realizations to ascertain whether they have identical power spectral densities. A binary hypothesis testing approach is formulated and a generalized likelihood ratio test (GLRT) is derived. An asymptotic analytical solution for calculating the test threshold is provided. Th...

Detection of cyclostationary primary user (PU) signals in colored Gaussian noise for cognitive radio systems is considered based on looking for a cycle frequency at a particular time lag in the cyclic autocorrelation function (CAF) of the noisy PU signal. We explicitly exploit the knowledge that under the null hypothesis of PU signal absent, the me...

We consider joint design of source and relay pre-coders in a cognitive multiuser two-way relay system, which supports simultaneous transmission of multiple secondary users concurrently with primary network with the help of a relay node. The design criterion is to minimize the sum mean square error (MSE) of all users under a transmit power constrain...

We investigate a spectrum sensing method based on asymptotic analysis of the discrete Fourier transform of the received multiantenna signal, possibly non-Gaussian, for flat-fading primary user signals in white noise under noise variance uncertainty. The proposed approach is based on the generalized likelihood ratio test (GLRT) paradigm for a restri...

We consider joint optimization of spectrum sensing, channel access and power allocation in a multi-band cognitive radio network. Instead of making hard binary decisions as in traditional hypothesis testing spectrum sensing schemes, a soft spectrum sensing concept using the continuous-valued sensing test statistics is considered. The channel access...

One of the first steps to be accomplished by a cognitive user in cognitive radio applications is spectrum sensing: analysis of the received electromagnetic transmissions to search for unoccupied spectrum bands (spectrum holes). Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been propose...

We consider a physical layer approach to enhance wireless security by using the unique wireless channel state information (CSI) of a legitimate user to authenticate subsequent transmissions from this user, thereby denying access to any spoofer whose CSI would significantly differ from that of the legitimate user by virtue of a different spatial loc...

Detection of cyclostationary primary user (PU) signals in white Gaussian noise for cognitive radio systems is considered based on looking for a cycle frequency at a particular time lag in the cyclic autocorrelation function (CAF) of the noisy PU signal. We explicitly exploit the knowledge that under the null hypothesis of PU signal absent, the meas...

Cognitive radio allows for usage of licensed fre- quency bands by unlicensed users when the licensed spectrum bands are unoccupied. Therefore, one of the first critical steps to be accomplished by a cognitive user is spectrum sensing: search for unoccupied spectrum bands (spectrum holes). A popular approach is that of energy detection whose impleme...

Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been proposed for multiple antenna spectrum sensing in cognitive radios. These approaches are suitable for flat-fading channels in white noise with equal noise variances across antennas; knowledge of the noise variance is not required, unli...

Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been proposed for multiple antenna spectrum sensing in cognitive radios. These approaches are suitable for flat-fading channels in white noise with equal noise variances across antennas; knowledge of the noise variance is not required, unli...

Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been pro posed for multiple antenna spectrum sensing in cognitive radios. These approaches are suitable for flat-fading channels in white noise with equal noise variances across antennas; knowledge of the noise variance is not required, unl...

This paper considers spectrally efficient anti- jamming system design based on code-controlled frequency hopping. Unlike conventional frequency hopping systems where hopping patterns are determined by preselected pseudo-random sequences, in the proposed scheme, part of source information is passed through a block encoder, and used to determine the...

Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been proposed for multiple antenna spectrum sensing in cognitive radios. These approaches are suitable for flat-fading channels in white noise with equal noise variances across antennas; knowledge of the noise variance is not required, unli...

One of the first steps to be accomplished by a cognitive user in cognitive radio applications is spectrum sensing: analysis of the received electromagnetic transmissions to search for unoccupied spectrum bands (spectrum holes). We propose two spectrum sensing methods based on comparing the power spectral densities estimated from data acquired over...

We present a turbo (iterative) equalization receiver with fixed-lag nonlinear Kalman filtering for coded data transmission over doubly-selective channels. The proposed receiver exploits the complex exponential basis expansion model (CEBEM) for the overall channel variations, and an autoregressive (AR) model for the BEM coefficients. We extend an ex...

Three versions of a novel adaptive channel estimation approach, exploiting the over-sampled complex exponential basis expansion model (CE-BEM), is presented for doubly selective channels, where we track the BEM coefficients rather than the channel tap gains. Since the time-varying nature of the channel is well captured in the CE-BEM by the known ex...

We consider doubly selective multiuser/multiple-input-multiple-output (MIMO) channel estimation and data detection using superimposed training. The time- and frequency-selective fading channel is assumed to be well described by a discrete prolate spheroidal basis expansion model (DPS-BEM) using Slepian sequences as basis functions. A user-specific...

We consider a physical layer approach to enhance wireless security by using the unique wireless channel state information (CSI) of a legitimate user to authenticate subsequent transmissions from this user, thereby denying access to any spoofer whose CSI would significantly differ from that of the legitimate user by virtue of a different spatial loc...

We consider a decision-directed tracking approach to doubly-selective channel estimation exploiting the complex exponential basis expansion model (CE-BEM). The time-varying nature of the channel is well captured by the CE-BEM while the time-variations of the (unknown) BEM coefficients are likely much slower than those of the channel. We track the B...

We consider a physical layer approach to enhance wireless security by using the unique wireless channel state information (CSI) of a legitimate user to authenticate subsequent transmissions from this user, thereby denying access to any spoofer whose CSI would significantly differ from that of the legitimate user by virtue of a different spatial loc...

We present an adaptive soft-input soft-output (SISO) turbo equalization receiver for doubly-selective multiple-input-multiple-output (MIMO) channels. The proposed receiver exploits the complex exponential basis expansion model (CE-BEM) for the overall channel variations, and an autoregressive (AR) model for the BEM coefficients. We extend an existi...

We present a decision-directed tracking approach to doubly-selective channel estimation exploiting the complex exponential basis expansion model (CE-BEM). The time-varying nature of the channel is well captured by the CE-BEM while the time-variations of the (unknown) BEM coefficients are likely much slower than those of the channel. We track the BE...

In this correspondence, an approach to enhance the quality of superimposed training (ST) based channel estimation procedures is proposed. The approach is based on postprocessing the estimated channel. This postprocessing is performed with the projection of the estimated channel onto a set of orthogonal functions known as the Universal Basis (UB), t...

We present an adaptive soft-input soft-output (SISO) turbo equalization receiver for doubly-selective channels. The proposed receiver exploits the complex exponential basis expansion model (CE-BEM) for the overall channel variations, and an autoregressive (AR) model for the BEM coefficients. We extend an existing turbo equalization approach based o...

An adaptive MIMO channel estimation scheme, exploiting the oversampled complex exponential basis expansion model (CE-BEM), is presented for doubly-selective fading channels where we track the BEM coefficients. The time-varying nature of the channel is well captured by the CE-BEM while the time-variations of the (unknown) BEM coefficients are likely...

In this paper, we exploit the Kalman filter as a time-varying linear minimum mean-square error equalizer for doubly-selective fading channels. We use a basis expansion model (BEM) to approximate the doubly-selective channel impulse response. Several time-varying linear equalizers have been proposed in the literature where both the channel and the e...

Channel estimation and data detection for frequency-selective time-varying channels are considered using superimposed training. We employ a discrete prolate spheroidal basis expansion model (DPS-BEM) to describe the time-varying channel. A periodic (nonrandom) training sequence is arithmetically added (superimposed) at low power to the information...

We consider decision feedback equalization of doubly selective channels modeled via basis expansion models (BEM). Recently there has been some interest in designing time-variant serial FIR (finite impulse response) decision feedback equalizers (DFE) using complex exponential (CE-) BEMs for equalizers in addition to using CE-BEM for modeling the cha...

An adaptive channel estimation scheme, exploiting the over-sampled complex exponential basis expansion model (CE-BEM), is presented for doubly-selective channels where we track the BEM coefficients via a multiple model approach. In the past work the number of BEM coefficients used to model the doubly-selective channels for channel estimation has be...

We present a (suboptimal) filtering algorithm for tracking highly maneuvering targets in a cluttered environment using multiple sensors. We concentrate on two targets which temporarily move in close formation, giving rise to a single detection due to the resolution limitations of the sensor. The filtering algorithm is developed by applying the basi...

An adaptive channel estimation scheme, exploiting the over- sampled complex exponential basis expansion model (CE- BEM), is presented for doubly-selective channels where we track the BEM coefficients. We extend/modify the subblock- wise tracking method using time-multiplexed (TM) training recently proposed by S. He and J. K. Tugnait (2007). Two fin...

We present a subblock-wise tracking approach to doubly-selective MIMO channel estimation, exploiting the oversampled complex exponential basis expansion model (CE-BEM) for the overall channel variations, and an autoregressive (AR) model to update the BEM coefficients. The time-varying nature of the channel is well captured by the CE-BEM while the t...

We present a decision-directed tracking approach to doubly-selective channel estimation, exploiting the complex exponential basis expansion model (CE-BEM) for overall channel variations, and an autoregressive (AR) model to update the BEM coefficients. We track the BEM coefficients via Kalman filtering, aided by symbol decisions from a decision-feed...

We present a decision-directed tracking approach to doubly-selective MIMO channel estimation, exploiting the complex exponential basis expansion model (CE-BEM) for the overall channel variations, and an autoregressive (AR) model to update the BEM coefficients. We track the BEM coefficients via Kalman filtering, aided by symbol decisions from a deci...

Channel estimation for single-user frequency- selective time-varying channels is considered using superimposed training. The time-varying channel is assumed to be well- approximated by a complex exponential basis expansion model (CE-BEM). A periodic (non-random) training sequence is arithmetically added (superimposed) at low power to the informatio...

We present a novel approach to doubly-selective channel estimation exploiting the complex exponential basis expansion model (CE-BEM) for the overall time-variant channel and an autoregressive (AR) model for the BEM coefficients. Since the time-varying nature of the channel is well captured in CE-BEM by the known exponential basis functions, the tim...

Channel estimation for single-input multiple-output time-invariant channels is considered using superimposed training. A periodic (nonrandom) training sequence is arithmetically added (superimposed) at low power to the information sequence at the transmitter before modulation and transmission. We extend a recently proposed first-order statistics-ba...