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Terahertz (THz) non-destructive evaluation (NDE) has shown great promise for applications in manufacturing, security screening, and medical imaging. However, interpretation of the THz A-scans is complicated by a number of factors. Other researchers have applied signal processing techniques that improve object boundary detection, but still rely on human interpretation without a statistical framework...
To overcome the inter-carrier interference (ICI) of orthogonal frequency division multiplexing (OFDM) systems due to the carrier frequency offset (CFO), an ICA-based carrier synchronization method is proposed. Independent component analysis (ICA) is also known as blind source separation (BSS), which depends on the independence of source signals to separate or extract latent signals of interest. In...
Automatic Modulation Classification (AMC) is a key enabling technology in Cognitive Radio (CR) Networks. The ability of CR transceivers to detect and classify unknown wireless signals has various applications in civilian and military domains. Performance of AMC degrades severely under low Signal-to-Noise Ratio (SNR) and variable channel conditions. Cooperative classification has been presented as...
Both N-continuous OFDM and N-continuous symbol padding OFDM (NCSP-OFDM) are modulation techniques that achieve a low sidelobe transmission signal. This study compares the timing synchronization performance of these modulation techniques by using a simple non-data-aided algorithm. The experimental results indicate that the timing metric curve of N-continuous OFDM becomes flat near the ideal timing...
This paper considers target localization in passive multiple-input multiple-output (MIMO) radar sensor networks comprised of multiple non-cooperative transmitters and multiple multichannel receivers. The maximum likelihood estimator is derived for direct estimation of target position and velocity in Cartesian space using all measurement data. Localization performance is shown to vary significantly...
We present an improved symbol synchronization method based on maximum likelihood estimator for OFDM systems. The approach proposed here is an improvement of the previously proposed estimation method given by Van de Beek, Sandel and Borjesson (see IEEE Trans. On Signal Processing, vol.45, no.3, p. 1800-05, 1997). Our research indicates that the correlation coefficient in the ML estimator is the function...
A detailed simulative and experimental analysis of different CPE schemes for 64-QAM systems is presented. The best compromise between linewidth tolerance and complexity is achieved using a recently proposed multi-stage architecture, based on a modification of the standard V&V algorithm.
This paper focuses on the channel estimation for residual self-interference cancellation at the baseband in a full-duplex transceiver. In particular, we analyze and develop a semi-blind maximum-likelihood algorithm to jointly estimate both the residual self-interference channel and intended signal channel based on the perfectly known transmitted symbols from its own transmitter, and both known pilot...
Advanced co-channel interference aware signal detection has drawn research attention during the recent development of Long Term Evolution-Advanced (LTE-A) systems and the interference-aware communications (IAC) is currently being studied by 3GPP. This paper investigates link performance abstraction for the IAC systems employing maximum- likelihood detector (MLD). The link performance of MLD can be...
We investigate orthogonal frequency-division multiplexing (OFDM) systems that operate with limited or insufficient cyclic prefix (CP). Using a shorter CP can enable a significant reduction in bandwidth usage or enable range extension for OFDM networks. The cost is increased inter-symbol interference (ISI) and inter-carrier interference (ICI). Here, the effect of ICI and ISI on the received signal...
In this paper, we study the performance of sequential detectors (SDs) in cooperative cognitive radio networks. In the fixed sample size (FSS) detectors, the generalized likelihood ratio (GLR) test, obtained through substituting the maximum likelihood (ML) estimates of the unknown parameters in the likelihood functions, is a current alternative when deriving the uniformly most powerful (UMP) test is...
Orthogonal Frequency Division Multiplexing (OFDM) is a common used technology for communication systems nowadays. Besides the synchronization of OFDM based receivers, the estimation of the noise variance as well as the corresponding signal-to-noise ratio (SNR) is a challenging issue, especially under dispersive fading channel conditions. In this paper the principle of blind OFDM synchronization via...
In this paper, the problem of signal-to-noise ratio (SNR) estimator design for a single-input multiple-output (SIMO) communication system employing non-coherent M-ary frequency shift keying (NCMFSK) modulation scheme is considered. The transmitted signal undergoes Rayleigh fading and additive white Gaussian noise (AWGN) and is received at a receiver with L diversity branches. Closed-form expressions...
Detecting signal in fMRI studies relies on the classical testing framework developed for Gaussian signals. Unfortunately, fMRI signals are amplitude measurements such that the signal follows a Rice distribution. The classical t-test used for detection performs reasonably well for signals with a high Signal-to-Noise Ratio (SNR). To accurately detect the voxels at the border of the brain region of interest,...
The problem of detecting significant brain activity upon stimulus in functional Magnetic Resonance Imaging (fMRI) data is tackled by a statistical data analysis for which the signal's amplitude is required. From literature, it is known that fMRI data follow a Rice distribution. Hence, for fMRI signal detection first the parameters of the Rice distribution need to be estimated. Different methods exist...
Electroencephalogram (EEG) is a brain signal that has much information of human thought and health. For this reason, the current study on clinical brain research and brain machine interface (BMI) uses EEG signal in many applications. Due to the significant noise in EEG, signal processing to enhance signal to noise power ratio (SNR) is necessary for EEG research. The typical method is averaging many...
In this paper, asynchronous sensor localization using time-of-arrival (TOA) measurements is studied. Accurate TOA-based localization requires perfect timing synchronization between the source and anchor nodes. In asynchronous networks, the anchor nodes are assumed to be synchronized, while the clock of the source node needs be synchronized with those of the anchor nodes. Although synchronization and...
For a connected network, consensus based algorithms guarantee that local estimates are iteratively shared and refined among neighbors to reach the same weighted average on all nodes. Parameter estimation for linear models are common problems where average consensus are routinely adopted to mimic a centralized approach without the need of any fusion center. Convergence speed, accuracy and the amount...
Motivated primarily by electronic surveillance applications, but also by other potential uses in passive exploitation of radio frequency (RF) signals, this paper considers the problems of detecting the presence of and characterizing a radar transmitter using data collected at a spatially distributed suite of receivers. A characterization of a particular interest is determining the rank of the transmitted...
This paper addresses the multi-target localization problem for noncoherent multiple-input multiple-output (MIMO) radar with widely separated antennas. To this end, we first adopt a high-dimensional parameter vector, which is the concatenation of the parameters to be estimated for individual targets, and then propose a novel multi-target localization algorithm by estimating the high-dimensional parameter...
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