Erchin Serpedin

The large influx of data from high-throughput genomic and proteomic technologies has encouraged the researchers to seek approaches for understanding the structure of gene regulatory networks and proteomic networks. This work reviews some of the most important statistical methods used for modeling of gene regulatory networks (GRNs) and protein-protein interaction (PPI) networks. The paper focuses on the recent advances in the statistical graphical modeling techniques, state-space representation models, and information theoretic methods that were proposed for inferring the topology of GRNs. It appears that the problem of inferring the structure of PPI networks is quite different from that of GRNs. Clustering and probabilistic graphical modeling techniques are of prime importance in the statistical inference of PPI networks, and some of the recent approaches using these techniques are also reviewed in this paper. Performance evaluation criteria for the approaches used for modeling GRNs and PPI networks are also discussed.

Recently, wireless sensor networks (WSNs) have drawn great interest due to their outstanding monitoring and management potential in medical, environmental and industrial applications. Most of the applications that employ WSNs demand all of the sensor nodes to run on a common time scale, a requirement that highlights the importance of clock synchronization. The clock synchronization problem in WSNs is inherently related to parameter estimation. The accuracy of clock synchronization algorithms depends essentially on the statistical properties of the parameter estimation algorithms. Recently, studies dedicated to the estimation of synchronization parameters, such as clock offset and skew, have begun to emerge in the literature. The aim of this article is to provide an overview of the state-of-the-art clock synchronization algorithms for WSNs from a statistical signal processing point of view. This article focuses on describing the key features of the class of clock synchronization algorithms that exploit the traditional two-way message (signal) exchange mechanism. Upon introducing the two-way message exchange mechanism, the main clock offset estimation algorithms for pairwise synchronization of sensor nodes are first reviewed, and their performance is compared. The class of fully-distributed clock offset estimation algorithms for network-wide synchronization is then surveyed. The paper concludes with a list of open research problems pertaining to clock synchronization of WSNs.

Recent results have pointed out the importance of inducing
cyclostationarity at the transmitter for blind identification of FIR communication
channels. The present paper considers the blind identification
problem of an ARMA(p; q) channel by exploiting the cyclostationarity
induced at the transmitter through periodic encoding of the input. It
is shown that causal and stable ARMA(p; q) channels can be uniquely
identified from the output second-order cyclic statistics, irrespective of
the location of channel poles and zeros and color of additive stationary
noise, provided that the cyclostationary input has at least q + 1 nonzero
cycles.
I

— Truncated Volterra expansions model nonlinear systems encountered with satellite communications, magnetic recording channels, and physiological processes. A general approach for blind deconvolution of single-input multiple-output Volterra finite impulse response (FIR) systems is presented. It is shown that such nonlinear systems can be blindly equalized using only linear FIR filters. The approach requires that the Volterra kernels satisfy a certain coprimeness condition and that the input possesses a minimal persistence-of-excitation order. No other special conditions are imposed on the kernel transfer functions or on the input signal, which may be deterministic or random with unknown statistics. The proposed algorithms are corroborated with simulation examples.

The development of tiny, low-cost, low-power and multifunctional sensor nodes equipped with sensing, data processing, and communicating components, have been made possible by the recent advances in micro-electro-mechanical systems (MEMS) technology. Wireless sensor networks (WSNs) assume a collection of such tiny sensing devices connected wirelessly and which are used to observe and monitor a variety of phenomena in the real physical world. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. This paper reviews the existing clock synchronization protocols for WSNs and the methods of estimating clock offset and clock skew in the most representative clock synchronization protocols for WSNs.

Motivation: Network component analysis (NCA) is an efficient method of reconstructing the transcription factor activity (TFA), which makes use of the gene expression data and prior information available about transcription factor (TF)-gene regulations. Most of the contemporary algorithms either exhibit the drawback of inconsistency and poor reliability, or suffer from prohibitive computational complexity. In addition, the existing algorithms do not possess the ability to counteract the presence of outliers in the microarray data. Hence, robust and computationally efficient algorithms are needed to enable practical applications. Results: We propose ROBust Network Component Analysis (ROBNCA), a novel iterative algorithm that explicitly models the possible outliers in the microarray data. An attractive feature of the ROBNCA algorithm is the derivation of a closed form solution for estimating the connectivity matrix, which was not available in prior contributions. The ROBNCA algorithm is compared to FastNCA and the Non-iterative NCA (NI-NCA). ROBNCA estimates the TF activity profiles as well as the TF-gene control strength matrix with a much higher degree of accuracy than FastNCA and NI-NCA, irrespective of varying noise, correlation and/or amount of outliers in case of synthetic data. The ROBNCA algorithm is also tested on Saccharomyces Cerevisiae data and Eschericia coli data and it is observed to outper-form the existing algorithms. The run time of the ROBNCA algorithm is comparable to that of FastNCA, and is hundreds of times faster than NI-NCA. Availability: The ROBNCA software is available at

Motivation: A central question in reverse engineering of genetic networks consists in determining the dependencies and regulating relationships among genes. This paper addresses the problem of inferring genetic regulatory networks from time-series gene-expression profiles. By adopting a probabilistic modeling framework compatible with the family of models represented by dynamic Bayesian networks and probabilistic Boolean networks, this paper proposes a network inference algorithm to recover not only the direct gene connectivity but also the regulating orientations. Results: Based on the minimum description length principle, a novel network inference algorithm is proposed that greatly shrinks the search space for graphical solutions and achieves a good trade-off between modeling complexity and data fitting. Simulation results show that the algorithm achieves good performance in the case of synthetic networks. Compared with existing state-of-the-art results in the literature , the proposed algorithm exceptionally excels in efficiency, accuracy, robustness and scalability. Given a time-series dataset for Drosophila melanogaster, the paper proposes a genetic regulatory network involved in Drosophila's muscle development.

— Recent results have pointed out the importance of inducing cyclostationarity at the transmitter for blind identification and equalization of communication channels. This paper addresses blind channel identification and equalization relying on the modulation induced cyclostationarity, without introducing redundancy at the transmitter. It is shown that single-input single-output channels can be identified uniquely from output second-order cyclic statistics, irrespective of the location of channel zeros, color of additive stationary noise, or channel order overesti-mation errors, provided that the period of modulation-induced cyclostationarity is greater than half the channel length. Linear, closed-form, nonlinear correlation matching, and subspace-based approaches are developed for channel estimation and are tested using simulations. Necessary and sufficient blind channel iden-tifiability conditions are presented. A Wiener cyclic equalizer is also proposed.

The fundamental role of signal processing techniques was demonstrated
in the context of clock synchronization in WSNs. This
article explains many existing intuitive clock synchronization
protocols and gives some directions to the necessary ingredients
for devising an optimal estimator operating under an unconventional
environment. However, centralized signal processing
techniques can only help solving the problem of node-to-node
synchronization and possible ad hoc extensions to network-wide
synchronization. The next important step is the application of
decentralized signal processing techniques (e.g., distributed estimation
and detection) to the clock synchronization problem, and
this naturally results in desirable distributed clock synchronization
algorithms. Furthermore, distributed signal processing techniques
will reveal the optimal way of information passing, thus
saving unnecessary communication overhead.

—Orthogonal frequency-division multiplexing (OFDM)-based ultra-wide-band (UWB) transceivers hold the promise to revolutionize the next generation of short-range wireless networks and to be adopted in electronics products for both civil and military applications. For the UWB transceivers to coexist with nearby devices, it is necessary to design efficient UWB receivers whose operation is robust to narrowband interferences (NBI). This paper conducts an in-depth analysis to establish the impacts of NBI on the performance of an OFDM-UWB receiver. A comprehensive study to assess the effects of NBI on the quantization noise in the analog-to-digital converter (ADC), timing, and carrier acquisition is presented. The analytical results show that the efficiency of the ADC is degraded by NBI, although this problem could be slightly remedied by an adaptive autogain controller (AGC). It is also found that, compared with the conventional autocorrelation-based acquisition scheme, the pseudonoise (PN) sequence matched-filtering-based acquisition scheme presents higher robustness to NBI. Nevertheless, both these two acquisition schemes fail at high interference levels. As a conclusion, it is critical to develop novel and low-complexity NBI mitigation schemes for OFDM-UWB receivers that take into account the impacts introduced by NBI. Index Terms—Analog-to-digital converter (ADC), carrier frequency offset, narrowband interference, orthogonal frequency-division multiplexing (OFDM), quantization noise, timing synchronization , ultra-wide-band.

The present bibliography represents a comprehensive list of references on cyclostationarity and its applications. An attempt has been made to make this bibliography complete by listing most of the existing references up to the year 2005 and by providing a detailed classification group.

—A new decision-directed (DD) synchronization scheme is proposed for joint estimation of carrier frequency offset (CFO) and sampling clock frequency offset (SFO) in orthogonal frequency-division multiplexing (OFDM) systems. By exploiting the hard decisions, we report accurate estimators of residual CFO and small SFO. The performance analysis and simulation results indicate that the proposed novel DD scheme achieves much better performance than the conventional pilot-based schemes in both additive white Gaussian noise and frequency-selective channels. Index Terms—Carrier frequency offset (CFO), fast Fourier transform (FFT), orthogonal frequency-division multiplexing (OFDM), sampling clock frequency offset (SFO), synchronization.

—Large quadrature amplitude modulation (QAM) constellations are currently used in throughput efficient high-speed communication applications such as digital TV. For such large signal constellations, carrier-phase synchronization is a crucial problem because for efficiency reasons, the carrier acquisition must often be performed blindly, without the use of training or pilot sequences. The goal of the present paper is to provide thorough performance analysis of the blind carrier phase estima-tors that have been proposed in the literature and to assess their relative merits.

—Nondata-aided carrier frequency offset and symbol timing delay estimators for linearly modulated waveforms transmitted through flat-fading channels have been recently developed by exploiting the received signal's second-order cyclostationary statistics. The goal of this paper is to establish and analyze the asymptotic (large sample) performance of the estimators as a function of the pulse shape bandwidth and the oversampling factor. It is shown that selecting larger values for the oversampling factor does not improve the performance of these estimators, and the accuracy of symbol timing delay estimators improves as the pulse shape bandwidth increases.

This paper proposes a novel algorithm for inferring gene regulatory networks which makes use of cubature Kalman filter (CKF) and Kalman filter (KF) techniques in conjunction with compressed sensing methods. The gene network is described using a state-space model. A nonlinear model for the evolution of gene expression is considered, while the gene expression data is assumed to follow a linear Gaussian model. The hidden states are estimated using CKF. The system parameters are modeled as a Gauss-Markov process and are estimated using compressed sensing-based KF. These parameters provide insight into the regulatory relations among the genes. The Cramér-Rao lower bound of the parameter estimates is calculated for the system model and used as a benchmark to assess the estimation accuracy. The proposed algorithm is evaluated rigorously using synthetic data in different scenarios which include different number of genes and varying number of sample points. In addition, the algorithm is tested on the DREAM4 in silico data sets as well as the in vivo data sets from IRMA network. The proposed algorithm shows superior performance in terms of accuracy, robustness, and scalability.

In this paper, the data aided (DA) and non-data aided (NDA) maximum likelihood (ML) symbol timing estimators and their corresponding conditional Cramer–Rao bound (CCRB) and modified Cramer–Rao bound (MCRB) in multiple-input-multiple-output (MIMO) correlated flat-fading channels are derived. It is shown that the approximated ML algorithm in References [4,13] is just a special case of the DA ML estimator; while the extended squaring algorithm in Reference [14] is just a special case of the NDA ML estimator. For the DA case, the optimal orthogonal training sequences are also derived. It is found that the optimal orthogonal sequences resemble the Walsh sequences, but present different envelopes. Simulation results under different operating conditions (e.g. number of antennas and correlation between antennas) are given to assess and compare the performances of the DA and NDA ML estimators with respect to their corresponding CCRBs and MCRBs. It is found that (i) the mean square error (MSE) of the DA ML estimator is close to the CCRB and MCRB, (ii) the MSE of the NDA ML estimator is close to the CCRB but not to the MCRB, (iii) the MSEs of both DA and NDA ML estimators are approximately independent of the number of transmit antennas and are inversely proportional to the number of receive antennas, (iv) correlation between antennas has little effect on the MSEs of DA and NDA ML estimators and (v) DA ML estimator performs better than NDA ML estimator at the cost of lower transmission efficiency and higher implementation complexity.

To avoid significant losses that might be induced by a narrow-band interference (NBI) on the performance of a multi-band (MB) OFDM ultra wideband (UWB) receiver, efficient NBI mitigation schemes are required. This paper proposes a novel mixed-mode NBI suppression scheme that relies on the cooperation between a digital NBI detector and an adaptive analog notch filter. Simulation results show that the proposed mixed-mode suppression scheme improves the performance of the digital frequency exci-sion scheme in a MB-OFDM UWB receiver by as much as an equivalent signal-to-interference ratio gain of 9 dB.

—Orthogonal frequency-division multiplexing (OFDM)-based ultra-wide-band (UWB) transceivers hold the promise to revolutionize the next generation of short-range wireless networks and to be adopted in electronics products for both civil and military applications. For the UWB transceivers to coexist with nearby devices, it is necessary to design efficient UWB receivers whose operation is robust to narrowband interferences (NBI). This paper conducts an in-depth analysis to establish the impacts of NBI on the performance of an OFDM-UWB receiver. A comprehensive study to assess the effects of NBI on the quantization noise in the analog-to-digital converter (ADC), timing, and carrier acquisition is presented. The analytical results show that the efficiency of the ADC is degraded by NBI, although this problem could be slightly remedied by an adaptive autogain controller (AGC). It is also found that, compared with the conventional autocorrelation-based acquisition scheme, the pseudonoise (PN) sequence matched-filtering-based acquisition scheme presents higher robustness to NBI. Nevertheless, both these two acquisition schemes fail at high interference levels. As a conclusion, it is critical to develop novel and low-complexity NBI mitigation schemes for OFDM-UWB receivers that take into account the impacts introduced by NBI. Index Terms—Analog-to-digital converter (ADC), carrier frequency offset, narrowband interference, orthogonal frequency-division multiplexing (OFDM), quantization noise, timing synchronization , ultra-wide-band.

—Orthogonal frequency-division multiplexing (OFDM)-based ultra-wide-band (UWB) transceivers hold the promise to revolutionize the next generation of short-range wireless networks and to be adopted in electronics products for both civil and military applications. For the UWB transceivers to coexist with nearby devices, it is necessary to design efficient UWB receivers whose operation is robust to narrowband interferences (NBI). This paper conducts an in-depth analysis to establish the impacts of NBI on the performance of an OFDM-UWB receiver. A comprehensive study to assess the effects of NBI on the quantization noise in the analog-to-digital converter (ADC), timing, and carrier acquisition is presented. The analytical results show that the efficiency of the ADC is degraded by NBI, although this problem could be slightly remedied by an adaptive autogain controller (AGC). It is also found that, compared with the conventional autocorrelation-based acquisition scheme, the pseudonoise (PN) sequence matched-filtering-based acquisition scheme presents higher robustness to NBI. Nevertheless, both these two acquisition schemes fail at high interference levels. As a conclusion, it is critical to develop novel and low-complexity NBI mitigation schemes for OFDM-UWB receivers that take into account the impacts introduced by NBI. Index Terms—Analog-to-digital converter (ADC), carrier frequency offset, narrowband interference, orthogonal frequency-division multiplexing (OFDM), quantization noise, timing synchronization , ultra-wide-band.

—Due to the huge bandwidth of ultra-wide-band (UWB) systems, in-band narrow-band interference (NBI) may hinder receiver performance. Sources of potential NBI that lie within the IEEE 802.15.3a UWB bandwidth are presented. To combat interference in multi-band orthogonal frequency-division multiplexing (MB-OFDM) UWB systems, an analog notch filter is designed to be included in the UWB receive chain. The filter's architecture is based on feedforward subtraction of the interference, and includes a least-mean-square (LMS) tuning scheme to match amplitudes of the two paths. An 8-bit discrete control is used to adjust the filter's center frequency across the UWB baseband. It was fabricated in TSMC's 0.18-m process, and experimental results are provided. Index Terms—Analog filters, least mean square (LMS), multi-band orthogonal frequency-division multiplexing (MB-OFDM), notch filters, ultra-wide-band (UWB).

This paper analyzes the impact of narrow-band interference (NBI) on the performance of multi-band (MB) OFDM ultra wideband communication systems. A comprehensive study of the effects of NBI on the analog-to-digital converter (ADC) and carrier synchronization algorithm is presented. The overall impact of NBI is demonstrated by quantifying the MB-OFDM receiver system level performance in terms of block error rate.

This paper performs a comprehensive performance analysis of a family of non-data-aided feedforward carrier frequency offset estimators for QAM signals transmitted through AWGN channels in the presence of unknown timing error. The proposed carrier frequency offset estimators are asymptotically (large sample) nonlinear least-squares estimators obtained by exploiting the fourth-order conjugate cyclostationary statistics of the received signal and exhibit fast convergence rates (asymptotic variances on the order of O(N −3), where N stands for the number of samples). The exact asymptotic performance of these estimators is established and analyzed as a function of the received signal sampling frequency, signal-to-noise ratio, timing delay, and number of symbols. It is shown that in the presence of intersymbol interference effects, the performance of the frequency offset estimators can be improved significantly by oversampling (or fractionally sampling) the received signal. Finally, simulation results are presented to corroborate the theoretical performance analysis, and comparisons with the modified Cramér-Rao bound illustrate the superior performance of the proposed nonlinear least-squares carrier frequency offset estimators.

— This paper analyzes the effects of the level of cooperation (LOC) on the performance of a practical cooperative coding scheme for frequency division half-duplex relay links in general wireless ad-hoc networks. The end-to-end bit error probability (BEP) and the corresponding optimum LOC minimizing the end-to-end BEP are investigated for specific realizations using a family of rate compatible punctured convolutional (RCPC) codes. This paper shows that the BEP of the cooperative coding scheme depends on the LOC and there exists an optimum LOC for every specific realization. Further, it is shown that more than a certain level of cooperation is required to achieve possible cooperative gains in practical signal-to-noise ratio (SNR) regions, and increasing LOC does not effect much on the BEP performance for sufficiently large LOCs.

Periodic modulation precoders allow blind identiica-tion of SISO channels from output second-order cyclic statistics, irrespective of the location of channel zeros, color of additive stationary noise, or channel order over-estimation errors. In this paper the performance of blind channel estimators relying on periodic precoders is investigated. Criteria for optimal designs of periodic modulation precoders are also presented.

Periodic modulation precoders allow blind identiica-tion of SISO channels from output second-order cyclic statistics, irrespective of the location of channel zeros, color of additive stationary noise, or channel order over-estimation errors. In this paper the performance of blind channel estimators relying on periodic precoders is investigated. Criteria for optimal designs of periodic modulation precoders are also presented.

The problem of clock offset estimation in a two-way timing exchange regime is considered when the likelihood function of the observation time stamps is exponentially distributed. In order to capture the imperfections in node oscillators, which render a time-varying nature to the clock offset, a novel Bayesian approach to the clock offset estimation is proposed using a factor graph representation of the posterior density. Message passing using the max-product algorithm yields a closed form expression for the Bayesian inference problem.

— In this letter, all the previously proposed digital blind feedforward symbol timing estimators employing second-order statistics are casted into a unified framework. The finite sample mean-square error (MSE) expression for this class of estimators is established. Simulation results are also presented to corroborate the analytical results. It is found that the feedforward conditional maximum likelihood (CML) estimator and the square law nonlinearity (SLN) estimator with a properly designed pre-filter perform the best and their performances coincide with the asymptotic conditional Cramer-Rao bound (CCRB), which is the performance lower bound for the class of estimators under consideration.

—This paper focuses on illustrating 1) the equivalence between Stein's identity and De Bruijn's identity, and 2) two extensions of De Bruijn's identity. First, it is shown that Stein's identity is equivalent to De Bruijn's identity under additive noise channels with specific conditions. Second, for arbitrary but fixed input and noise distributions under additive noise channels, the first derivative of the differential entropy is expressed by a function of the posterior mean, and the second derivative of the differential entropy is expressed in terms of a function of Fisher information. Several applications over a number of fields such as signal processing and information theory, are presented to support the usefulness of the developed results in this paper. Index Terms—Stein's identity, De Bruijn's identity, entropy power inequality (EPI), Costa's EPI, Fisher information inequality (FII), Cramér-Rao lower bound (CRLB), Bayesian Cramér-Rao lower bound (BCRLB)

— In this letter, all the previously proposed digital blind feedforward symbol timing estimators employing second-order statistics are casted into a unified framework. The finite sample mean-square error (MSE) expression for this class of estimators is established. Simulation results are also presented to corroborate the analytical results. It is found that the feedforward conditional maximum likelihood (CML) estimator and the square law nonlinearity (SLN) estimator with a properly designed pre-filter perform the best and their performances coincide with the asymptotic conditional Cramer-Rao bound (CCRB), which is the performance lower bound for the class of estimators under consideration.

—Clock synchronization is an important issue for the design of a network composed of small sensor nodes. Based on the two-way timing message exchange mechanism and assuming an exponential network delay distribution, many analytical results have been presented in the literature by applying the techniques from statistical signal processing. This paper derives the minimum variance unbiased estimator for the clock offset for both symmetric and asymmetric exponential delay cases. For the asymmetric delays, it is shown to be a function of both the minimum and the mean link delays. This result is a very significant contribution since only the minimum link delay observations have been used to estimate the clock offset in the past. For the symmetric case, it is shown to coincide with the maximum likelihood estimator. In addition, the result is also applicable to clock synchronization problem in general computer networks.

The paper discusses an adaptive multiuser receiver for CDMA systems in which the scaled unscented filter (SUF) and the square root unscented filter (SURF) are used for joint estimation and tracking of the code delays and multipath coefficients of the received CDMA signals. The proposed channel estimators are more near-far resistant than the conventional extended Kalman filter (EKF) and present lower complexity than the conventional particle filter (PF) based methods. To present meaningful performance measures, the modified Cramer–Rao lower bound (CRLB) and computational complexity metrics are derived for the proposed and existing channel estimators. Computer simulation results demonstrate the superior performance of the proposed channel estimators. The proposed estimators are also shown to exhibit lower complexity relative to the PF.

Although the existing time synchronization protocols in wireless sensor networks (WSNs) are efficient for short periods, many applications require long-term synchronization among the nodes, for example, coordinated sleep and wakeup modes, and synchronized sampling. In such applications, experiments have shown that even clock skew correction cannot maintain long-term clock synchronization and a quadratic model of clock variations can better capture the dynamics of the actual clock model involved, hence increasing the resynchronization period and conserving significant energy. This paper derives the maximum likelihood (ML) estimator for all the clock parameters in a two-way timing exchange model with exponential delays. The same estimation procedure can be applied to one-way timing exchange models with little modification.

Although the existing time synchronization protocols in wireless sensor networks (WSNs) are efficient for short periods, many applications require long-term synchronization among the nodes, for example, coordinated sleep and wakeup modes, and synchronized sampling. In such applications, experiments have shown that even clock skew correction cannot maintain long-term clock synchronization and a quadratic model of clock variations can better capture the dynamics of the actual clock model involved, hence increasing the resynchronization period and conserving significant energy. This paper derives the maximum likelihood (ML) estimator for all the clock parameters in a two-way timing exchange model with exponential delays. The same estimation procedure can be applied to one-way timing exchange models with little modification.

Recommended by Yuh-Shyan Chen This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection). The handoff trigger is decided based on the received signal strength (RSS). To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service), and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.

—Assuming that the network delays are normally distributed and the network nodes are subject to clock phase offset errors, the maximum likelihood estimator (MLE) and the Kalman filter (KF) have been recently proposed with the goal of maximizing the clock synchronization accuracy in wireless sensor networks (WSNs). However, because the network delays may assume any distribution and the performance of MLE and KF is quite sensitive to the distribution of network delays, designing clock synchronization algorithms that are robust to arbitrary network delay distributions appears as an important problem. Adopting a Bayesian framework, this paper proposes a novel clock synchronization algorithm, called the Iterative Gaussian mixture Kalman particle filter (IGMKPF), which combines the Gaussian mixture Kalman particle filter (GMKPF) with an iterative noise density estimation procedure to achieve robust performance in the presence of unknown network delay distributions. The Kullback-Leibler divergence is used as a measure to assess the departure of estimated observation noise density from its true expression. The posterior Cramér–Rao bound (PCRB) and the mean-square error (MSE) of IGMKPF are evaluated via computer simulations. It is shown that IGMKPF exhibits improved performance and robustness relative to MLE. The prior information plays an important role in IGMKPF. A MLE-based method for obtaining reliable prior information for clock phase offsets is presented and shown to ensure the convergence of IGMKPF.

This paper focuses on channel estimation in stan­ dard Ultra-Wide Band (UWB) based system. We consider Impulse Radio scheme relying on a binary Pulse Position Modulation as well as on a Spread-Spectrum Time-Hopping multiple access. We ad­ dress the closed-form expressions of the (resp. modified) Cramer­ Rao bound for the multi-path channel parameters in Data-aided (resp. Non-data-aided) context. The derivations have been devel­ oped by assuming the multiple-access interference as an additil'e white Gaussian noise. Com'erseIy the overlapping between signal echoes has been taken into account. Finally simplifications han been done by averaging the Fisher information matrix over the time-hopping random sequence as well as OH!r the symbol random sequence.

—This letter presents the design of an ultrawideband (UWB) band-notched wearable antenna and its validation using simulation and measurement results. The antenna can be used for ultrawideband applications, while rejecting the higher band assigned to wireless local area network (WLAN 5.25-GHz band). The presented return loss and radiation pattern results demonstrate that antenna properties have negligible variations when bent at different angles (a possible condition when placed on body) or placed in adverse conditions (under extreme heat and humidity). Moreover, reliable performance of antenna for on-body scenario makes the designed antenna a promising candidate for wearable applications.

In the realm of bioinformatics and computational biology, the most rudimentary data upon which all the analysis is built is the sequence data of genes, proteins and RNA. The sequence data of the entire genome is the solution to the genome assembly problem. The scope of this contribution is to provide an overview on the art of problem-solving applied within the domain of genome assembly in the next-generation sequencing (NGS) platforms. This article discusses the major genome assemblers that were proposed in the literature during the past decade by outlining their basic working principles. It is intended to act as a qualitative, not a quantitative, tutorial to all working on genome assemblers pertaining to the next generation of sequencers. We discuss the theoretical aspects of various genome assemblers, identifying their working schemes. We also discuss briefly the direction in which the area is headed towards along with discussing core issues on software simplicity.

Background: Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA) research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms. Results: To address these issues, herein we propose an analysis procedure designed to reduce suppression effect by focusing on a specific chemotherapeutic treatment, and to remove confounding effects such as batch effect, patient's age, and tumor stages. The proposed procedure starts with a batch effect adjustment, followed by a rigorous sample selection process. Then, the gene expression, copy number, and methylation profiles from the TCGA ovarian cancer dataset are analyzed using a semi-supervised clustering method combined with a novel scoring function. As a result, two molecular classifications, one with poor copy number profiles and one with poor methylation profiles, enriched with unfavorable scores are identified. Compared with the samples enriched with favorable scores, these two classifications exhibit poor progression-free survival (PFS) and might be associated with poor chemotherapy response specifically to the combination of paclitaxel and carboplatin. Significant genes and biological processes are detected subsequently using classical statistical approaches and enrichment analysis.

— This paper proposes to analyze the performance of a family of non-data aided open-loop carrier frequency offset (FO) estimators for a linearly modulated signal transmitted through an unknown flat-fading (possibly frequency-selective) channel. The exact asymptotic (large sample) performance of these estimators is established and analyzed as a function of the received signal sampling frequency, signal-to-noise ratio (SNR), timing delay, and number of samples (N). It is shown that in the presence of timing errors, the performance of the es-timators can be improved by oversampling (fractionally sampling) the received signal and by taking into account the entire cyclostationary information that is present in the received sequence.

— This paper focuses on channel estimation in standard Ultra-Wide Band (UWB) based system. We consider Impulse Radio scheme relying on a binary Pulse Position Modulation as well as on a Spread-Spectrum Time-Hopping multiple access. We address the closed-form expressions of the (resp. modified) Cramer-Rao bound for the multi-path channel parameters in Data-aided (resp. Non-data-aided) context. The derivations have been developed by assuming the multiple-access interference as an additive white Gaussian noise. Conversely the overlapping between signal echoes has been taken into account. Finally simplifications have been done by averaging the Fisher information matrix over the time-hopping random sequence as well as over the symbol random sequence.

—This letter deals with the compensation of the self-noise (jitter) in a nondata-aided (blind) feedforward symbol-timing estimator using two samples per symbol for linearly modulated waveforms transmitted through additive white Gaussian noise channels. The main contribution of this letter is the derivation of an appropriate prefilter to achieve nearly jitter-free digital blind feedforward timing recovery. Computer simulations illustrate that the proposed prefiltering scheme improves significantly the performance at mid and high signal-to-noise ratios.