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Signal Processing, IEEE Transactions on

Issue 4 • Date April 2009

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Displaying Results 1 - 25 of 39
  • Table of contents

    Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (132 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Signal Processing publication information

    Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • Unbiased FIR Filtering of Discrete-Time Polynomial State-Space Models

    Page(s): 1241 - 1249
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (641 KB) |  | HTML iconHTML  

    We address an unbiased finite impulse response (FIR) filter for discrete-time state-space models with polynomial representation of the states. The unique l-degree polynomial FIR filter gain and the estimate variance are found for a general case. The noise power gain (NG) is derived for white Gaussian noises in the model and in the measurement. The filter does not involve any knowledge about noise in the algorithm. It is unstable at short horizons, 2 les N les l, and inefficient (NG exceeds unity) in the narrow range l < N les Nb, where Nb is ascertained by the cross-components in the measurement matrix C. With N GtNb, the filter NG poorly depends on C and fits the asymptotic function (l +1)2/N . With very large N Gt>1, the estimate noise becomes negligible and the filter thus optimal in the sense of zero bias and zero noise. Having such properties, the proposed unbiased FIR filter fits well slowly changing with time models. An example is given for a two-state system. View full abstract»

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  • Subspace Partitioning for Target Detection and Identification

    Page(s): 1250 - 1259
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1198 KB) |  | HTML iconHTML  

    Detection of a given target or set of targets from observed data is a problem countered in many applications. Regardless of the algorithm selected, detection performance can be severely degraded when the subspace defined by the target data set is singular or ill conditioned. High correlations between target components and their linear combinations lead to false positives and misidentifications, especially for subspace-based detectors. In this paper, we propose a subspace partitioning scheme that allows for detection to be performed in a number of better conditioned subspaces instead of the original subspace. The proposed technique is applied to Raman spectroscopic data analysis. Through both simulation and experimental results, we demonstrate the improvement in the overall detection performance when using the proposed subspace partitioning scheme in conjunction with several subspace detection methods that are commonly used in practice. View full abstract»

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  • Improved, Approximate, Time-Domain ML Estimators of Chirp Signal Parameters and Their Performance Analysis

    Page(s): 1260 - 1272
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1057 KB) |  | HTML iconHTML  

    We derive an improved, approximate, maximum likelihood (ML) estimator for the parameters of a single-component chirp signal in the time domain, which has much lower computational complexity than that of the traditional estimators in the frequency domain. We term it the zero-order amplitude weighted phase-based estimator (AWPE). It is a weighted linear combination of the phases of the received signal samples, where the weights are determined by the amplitudes of the received signals. It achieves better performance than the only existing time-domain estimator in the literature that only exploits the phase information. A phase unwrapping (PU) algorithm is needed to recover the phase information correctly from the received signal samples. Several PU algorithms are compared and analyzed. A new, robust PU algorithm based on the first-order phase differences of the consecutive received signal samples is proposed. This new unwrapping algorithm has smaller PU failure probability than that based directly on the phases of the received signal samples. The need for PU can even be removed by using the second-order phase differences of the consecutive received signal samples. Two additional structures for the ML-based AWPE using the phase differences are derived starting from using the zero-order AWPE obtained. The first is based on the first-order phase differences and the second on the second-order phase differences. When the PU algorithm works perfectly, i.e., no phase unwrapping failure occurs, the estimators based on phase differences do not perform as well as the original one based on absolute phase information due to the increased noise variance. This is also applicable when the chirp parameters take on very small values. However, when no knowledge of the ranges of the chirp parameters is available, and the possible PU failures are taken into account, the estimators based on the phase differences could perform better. Performance analysis of the estimators is given based on- - an improved phase noise model. It is easy to verify that the estimates obtained are unbiased. The cramer-rao lower bound (CRLB) on the mean-square error (MSE) is derived. The MSE performance of the estimators approaches the CRLB at high signal-to-noise ratios. The variance performance of the estimators based on phase differences is analyzed, whose validity is demonstrated by simulation results. View full abstract»

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  • The Canonical Bicoherence—Part I: Definition, Multitaper Estimation, and Statistics

    Page(s): 1273 - 1284
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (822 KB) |  | HTML iconHTML  

    The central theme of this pair of papers (Parts I and II) [IEEE Transactions on Signal Processing, vol. 57, no. 4, April 2009] is a new definition: the canonical bicoherence, a combination of the canonical coherence and the bicoherence. The canonical bicoherence is an effective tool for analyzing quadratic nonlinearity in multivariate signals. In this first part, the definition and properties of the canonical bicoherence are presented. The feasibility of the canonical bicoherence in detecting quadratic phase coupling (QPC) of multivariate signals is explained theoretically, illustrated by an example, and verified by numerical simulations. Multitaper methods and a sequence of three singular value decompositions (SVD's) are used to estimate canonical bicoherences, to achieve reliable estimates with a reasonable amount of memory and computation time. Finally, we show that the canonical bicoherence estimate has an approximate asymptotic kappachinu 2-distribution, and the weighted jackknife method, used over tapers and segments, is applied to estimate variances of multitaper canonical bicoherence estimates. View full abstract»

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  • The Canonical Bicoherence—Part II: QPC Test and Its Application in Geomagnetic Data

    Page(s): 1285 - 1292
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (852 KB) |  | HTML iconHTML  

    In a companion paper [ldquoThe canonical bicoherence-Part I: Definition, multitaper estimation, and statistics,rdquo IEEE transactions on signal processing, vol. 57, no. 4, April 2009], we defined the canonical bicoherence (CBC), proposed its multitaper estimates, showed its feasibility to detect quadratic phase coupling (QPC) for multivariate random processes, and discussed its statistical properties. In this part, the canonical biphase (CBP) is defined, and a two-step QPC test is developed using the first canonical bicoherence and the first canonical biphase at prescribed significance levels. Detection probabilities of this test are given by Monte Carlo simulations. The canonical bicoherence is applied to analyze the possibility of quadratic phase couplings in the Earth's magnetic field. The results of simulations show that lower-frequency p -modes of the Sun may interact nonlinearly, producing intermodulation components at the sum and/or difference of fundamental frequency modes of oscillations. View full abstract»

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  • Stochastic MV-PURE Estimator— Robust Reduced-Rank Estimator for Stochastic Linear Model

    Page(s): 1293 - 1303
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (782 KB) |  | HTML iconHTML  

    This paper proposes a novel linear estimator named stochastic MV-PURE estimator, developed for the stochastic linear model, and designed to provide improved performance over the linear minimum mean square error (MMSE) Wiener estimator in cases prevailing in practical, real-world settings, where at least some of the second-order statistics of the random vectors under consideration are only imperfectly known. The proposed estimator shares its main mathematical idea and terminology with the recently introduced minimum-variance pseudo-unbiased reduced-rank estimator (MV-PURE), developed for the linear regression model. The proposed stochastic MV-PURE estimator minimizes the mean square error (MSE) of its estimates subject to rank constraint and inducing minimum distortion to the target random vector. Therefore, the stochastic MV-PURE combines the techniques of the reduced rank Wiener filter (named in this paper RR-MMSE) and the distortionless-constrained estimator (named in this paper C-MMSE), in order to achieve greater robustness against noise or model errors than RR-MMSE and C-MMSE. Furthermore, to ensure that the stochastic MV-PURE estimator combines the reduced-rank and minimum-distortion approaches in the MSE-optimal way, we propose a rank selection criterion which minimizes the MSE of the estimates obtained by the stochastic MV-PURE. As a numerical example, we employ the stochastic MV-PURE, RR-MMSE, C-MMSE, and MMSE estimators as linear receivers in a MIMO wireless communication system. This example is chosen as a typical signal processing scenario, where the statistical information on the data, on which the estimates are built, is only imperfectly known. We verify that the stochastic MV-PURE achieves the lowest MSE and symbol error rate (SER) in such settings by employing the proposed rank selection criterion. View full abstract»

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  • On the Constrained Stochastic Gradient Algorithm: Model, Performance, and Improved Version

    Page(s): 1304 - 1315
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1416 KB) |  | HTML iconHTML  

    This paper discusses the constrained stochastic gradient (CSG) algorithm used for controlling antenna arrays, aiming to maximize the signal-to-interference-plus-noise ratio (SINR) in mobile communications. Firstly, analytical expressions for the first moment of the weight vector and the SINR characteristic of the standard CSG algorithm are derived for two interferer signals, considering small step-size conditions and assuming Gaussian signal, interference, and noise. From these model expressions, the CSG algorithm performance is assessed, which predicts undesired behavior (termed here unbalanced behavior, pertaining to an unbalance between maximizing signal power and minimizing interference power) when one or more interference angles-of-arrival are close to the signal angle-of-arrival and the angle-of-arrival spreads of the involved signals are small. Finally, by using the model expressions, an improved CSG (ICSG) algorithm is proposed to compensate the unbalanced behavior of the standard CSG algorithm. The accuracy of the proposed model and the effectiveness of the modified algorithm are assessed through numerical simulations. View full abstract»

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  • The Quaternion LMS Algorithm for Adaptive Filtering of Hypercomplex Processes

    Page(s): 1316 - 1327
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1112 KB) |  | HTML iconHTML  

    The quaternion least mean square (QLMS) algorithm is introduced for adaptive filtering of three- and four-dimensional processes, such as those observed in atmospheric modeling (wind, vector fields). These processes exhibit complex nonlinear dynamics and coupling between the dimensions, which make their component-wise processing by multiple univariate LMS, bivariate complex LMS (CLMS), or multichannel LMS (MLMS) algorithms inadequate. The QLMS accounts for these problems naturally, as it is derived directly in the quaternion domain. The analysis shows that QLMS operates inherently based on the so called ldquoaugmentedrdquo statistics, that is, both the covariance E{ xx H} and pseudocovariance E{ xx T} of the tap input vector x are taken into account. In addition, the operation in the quaternion domain facilitates fusion of heterogeneous data sources, for instance, the three vector dimensions of the wind field and air temperature. Simulations on both benchmark and real world data support the approach. View full abstract»

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  • Low-Complexity Design of Variable Bandedge Linear Phase FIR Filters With Sharp Transition Band

    Page(s): 1328 - 1338
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (602 KB) |  | HTML iconHTML  

    This paper presents a very low-complexity design of variable bandedge linear phase finite-impulse-response (FIR) filters with fixed sharp transition width. The idea is to first decompose the input signal into several channels in the frequency domain. The channel(s) involved with the transition band of the variable filter due to the variation of the bandedge is (are) shaped to produce the required transition band, and then summed up with the channels involved with the passband of the variable filter to produce the required frequency response. The proposed variable filter has extremely low complexity when the transition band is sharp, if compared with other techniques such as the Farrow structure. It is possible that the computational complexity of the variable filter is even lower than that of a corresponding fixed filter with the same transition width and ripple specifications implemented in its direct form. View full abstract»

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  • Wavelet Codes: Detection and Correction Using Kalman Estimation

    Page(s): 1339 - 1350
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (547 KB) |  | HTML iconHTML  

    Wavelet codes encoded by uniform oversampled filter banks where the wavelet coefficients represent code symbols are decoded employing Kalman fixed-lag estimation procedures. The code symbol error estimates are based on the mean-squared error (MSE) criterion and are first used to detect the presence of large numerical errors. Then the correction of symbols uses these Kalman estimators directly. The wavelet code symbols are corrupted by low levels of processing noise continuously and occasionally by large disruptive errors, e.g., impulsive noise. The modeling variables have time-varying statistics allowing both types of errors to be handled naturally. Kalman time-varying tracking filters, which use wavelet syndromes as their measurement inputs, develop the fixed-lag smoothed estimates for the larger errors. The syndromes are also modeled as corrupted by processing noise modeling computational failure errors, large and small. Hypothesis detection methods are used to locate large errors and their statistics must include Kalman mismatch characteristics to be valid. Estimators from several adjacent lag positions assist in the detection procedures. Simulation results show correction accuracy in the time domain as well as on a MSE basis. Large classes of wavelet codes are designed using binary convolutional codes as starting points from which the proper filter weights for encoding and syndrome evaluating are determined. View full abstract»

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  • Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding

    Page(s): 1351 - 1362
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1681 KB) |  | HTML iconHTML  

    One of the tasks for which empirical mode decomposition (EMD) is potentially useful is nonparametric signal denoising, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show that although a direct application of this principle is not feasible in the EMD case, it can be appropriately adapted by exploiting the special characteristics of the EMD decomposition modes. In the same manner, inspired by the translation invariant wavelet thresholding, a similar technique adapted to EMD is developed, leading to enhanced denoising performance. View full abstract»

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  • Zero Assignment for Robust H_{2}/H_{\infty } Fault Detection Filter Design

    Page(s): 1363 - 1372
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1148 KB) |  | HTML iconHTML  

    In practical engineering, it is inevitable that a system is perturbed by noise signals. Unfortunately, H infin /H infin filtering may fail to detect some faults when the noise distribution matrix are the same as the fault distribution matrix. In this paper, it is shown that the dynamic feedback gain of a dynamic filter introduces additional zeros to the filter, and both the filter poles and the additional zeros can be assigned arbitrarily. In order to attenuate band-limited noises, the zero assignment technique is used, and an optimal dynamic fault detection filtering approach is proposed by locating the zeros to the noise frequencies and optimizing the poles. Compared to other dynamic filter design approaches, the zero assignment technique gives a better tradeoff between more design freedom and computation costs. As shown in the simulation, a better noise attenuation and fault detection performance have been obtained. The zero assignment in multivariable fault detection filter design would be the main contribution of this paper. View full abstract»

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  • Spectral Bias in Adaptive Beamforming With Narrowband Interference

    Page(s): 1373 - 1382
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1103 KB) |  | HTML iconHTML  

    It is shown that adaptive canceling arrays which track interference by regular updates of the beamformer weights can introduce a spectral null at the excised interference frequency. This PSD estimation bias effect we call ldquospectral scoopingrdquo is most prominent for narrowband interference (i.e., occupying only a few spectral bins at the desired PSD estimation resolution). Scooping is problematic in radio astronomy where bias in either the weak signal or noise floor spectra can corrupt the observation. The mathematical basis for scooping is derived, and an algorithm to eliminate it is proposed. Both simulated and real data experiments demonstrate the effectiveness of the proposed algorithm. View full abstract»

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  • On Spatial Aliasing in Microphone Arrays

    Page(s): 1383 - 1395
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1061 KB) |  | HTML iconHTML  

    Microphone arrays sample the sound field in both space and time with the major objective being the extraction of the signal propagating from a desired direction-of-arrival (DOA). In order to reconstruct a spatial sinusoid from a set of discrete samples, the spatial sampling must occur at a rate greater than a half of the wavelength of the sinusoid. This principle has long been adapted to the microphone array context: in order to form an unambiguous beampattern, the spacing between elements in a microphone array needs to conform to this spatial Nyquist criterion. The implicit assumption behind the narrowband beampattern is that one may use linearity and Fourier analysis to describe the response of the array to an arbitrary wideband plane wave. In this paper, this assumption is analyzed. A formula for the broadband beampattern is derived. It is shown that in order to quantify the spatial filtering abilities of a broadband array, the incoming signal's bifrequency spectrum must be taken into account, particularly for nonstationary signals such as speech. Multi-dimensional Fourier analysis is then employed to derive the broadband spatial transform, which is shown to be the limiting case of the broadband beampattern as the number of sensors tends to infinity. The conditions for aliasing in broadband arrays are then determined by analyzing the effect of computing the broadband spatial transform with a discrete spatial aperture. It is revealed that the spatial Nyquist criterion has little importance for microphone arrays. Finally, simulation results show that the well-known steered response power (SRP) method is formulated with respect to stationary signals, and that modifications are necessary to properly form steered beams in nonstationary signal environments. View full abstract»

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  • Time-Reversal Detection Using Antenna Arrays

    Page(s): 1396 - 1414
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1160 KB) |  | HTML iconHTML  

    The paper studies detection of a target buried in a rich scattering medium by time reversal. We use a multi-static configuration with receive and transmit arrays of antennas. In time reversal, the backscattered field is recorded, time reversed, and retransmitted (mathematically or physically) into the same scattering medium. We derive two array detectors: the time-reversal channel matched filter when the target channel response is known; and the time-reversal generalized-likelihood ratio test (TR-GLRT) when the target channel response is unknown. The noise added in the initial probing step to the time-reversal signal makes the analysis of the TR-GLRT detector non trivial. The paper derives closed form expressions for the signal-to-noise ratio gain provided by this detector over the corresponding conventional clutter subtraction energy detector in the two extreme conditions of weak and strong (electronic additive) noise and shows that time reversal provides, under weak noise, the optimal waveform shape to probe the environment. We analyze the impact of the array configuration on the detection performance. Finally, experiments with electromagnetic data collected in a multipath scattering laboratory environment confirm our analytical results. Under the realistic conditions tested, time reversal provides detection gains over conventional detection that range from 2 to 4.7 dB. View full abstract»

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  • New Algorithms for Designing Unimodular Sequences With Good Correlation Properties

    Page(s): 1415 - 1425
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1255 KB) |  | HTML iconHTML  

    Unimodular (i.e., constant modulus) sequences with good autocorrelation properties are useful in several areas, including communications and radar. The integrated sidelobe level (ISL) of the correlation function is often used to express the goodness of the correlation properties of a given sequence. In this paper, we present several cyclic algorithms for the local minimization of ISL-related metrics. These cyclic algorithms can be initialized with a good existing sequence such as a Golomb sequence, a Frank sequence, or even a (pseudo)random sequence. To illustrate the performance of the proposed algorithms, we present a number of examples, including the design of sequences that have virtually zero autocorrelation sidelobes in a specified lag interval and of long sequences that could hardly be handled by means of other algorithms previously suggested in the literature. View full abstract»

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  • Widely Linear Versus Linear Blind Multiuser Detection With Subspace-Based Channel Estimation: Finite Sample-Size Effects

    Page(s): 1426 - 1443
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (839 KB) |  | HTML iconHTML  

    In a recent paper [A. S. Cacciapuoti et al., ldquoFinite-Sample Performance Analysis of Widely Linear Multiuser Receivers in DS-CDMA Systems, IEEE Transactions on Signal Processing, vol. 56, no. 4, pp. 1572-1588, Apr. 2008], we presented the finite-sample theoretical performance comparison between linear (L) and widely linear (WL) minimum output-energy (MOE) receivers for direct-sequence code-division multiple-access (DS-CDMA) systems, worked out under the assumption that the channel impulse response of the desired user is exactly known. The main scope of this paper is to extend such an analysis, taking into account not only autocorrelation matrix (ACM) estimation effects, but also the accuracy of subspace-based blind channel estimation (CE). We aim to answer the two following questions: Which of the two estimation processes (ACM or CE) is the main source of degradation when implementing the receivers on the basis of a finite sample-size? Compared with the L-MOE one, is the finite-sample WL-MOE receiver with blind CE capable of achieving the performance gains predicted by the theory? To this goal, simple and easily interpretable formulas are developed for the signal-to-interference-plus-noise ratio (SINR) at the output of the L- and WL-MOE receivers with blind CE, when they are implemented using either the sample ACM or its eigendecomposition. In addition, the derived formulas, which are validated by simulations, allow one to recognize and discuss interesting tradeoffs between the main parameters of the DS-CDMA system. View full abstract»

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  • Timing Synchronization in Decode-and-Forward Cooperative Communication Systems

    Page(s): 1444 - 1455
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1017 KB) |  | HTML iconHTML  

    Cooperative communication systems have attracted much attention recently due to their desirable performance gain while using single antenna terminals. This paper addresses the joint timing and channel estimation problem, and furthermore the resynchronization of multiple timing offsets in a cooperative relay system. The estimations of timing and channel are conducted in two phases and the associated Cramer-Rao bounds (CRB) are derived for both phases. It is demonstrated that the conventional CRB is not valid for timing parameters under fading conditions, and a new bound called weighted Bayesian CRB is proposed. With the timing and channel estimates, a general framework of the resynchronization filter design is developed in order to compensate the multiple timing offsets at the destination. The proposed methods are applied to different scenarios with varying degrees of timing misalignment and are numerically shown to provide excellent performances that approach the perfectly synchronized case. View full abstract»

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  • A Flexible Peak-To-Average Power Ratio Reduction Scheme for OFDM Systems by the Adaptive Projected Subgradient Method

    Page(s): 1456 - 1468
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (961 KB) |  | HTML iconHTML  

    One of the main issues of the orthogonal frequency-division multiplexing (OFDM) modulation is the high peak-to-average power ratio (PAPR) of the transmitted signal, which adversely affects the complexity of power amplifiers. In this paper, we consider transmitters that reduce the PAPR by slightly disturbing the symbols in carriers used to transmit information and by sending dummy symbols-i.e., symbols not conveying information-in unused carriers. The optimal choice of the data and dummy symbols is determined by the solution of a convex optimization problem. To reduce the PAPR with low complexity, we apply a modified version of the adaptive projected subgradient method to a sequence of convex cost functions closely related to the original optimization problem. The resulting algorithm achieves near-optimal PAPR in practical scenarios, generalizes existing algorithms based on Polyak's method, and can easily handle multiple constraints. View full abstract»

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  • Finite Word Length Effects on Transmission Rate in Zero Forcing Linear Precoding for Multichannel DSL

    Page(s): 1469 - 1482
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (979 KB) |  | HTML iconHTML  

    Crosstalk interference is the limiting factor in transmission over copper lines. Crosstalk cancellation techniques show great potential for enabling the next leap in DSL transmission rates. An important issue when implementing crosstalk cancelation techniques in hardware is the effect of finite word length on performance. In this paper, we provide an analysis of the performance of linear zero-forcing precoders, used for crosstalk compensation, in the presence of finite word length errors. We quantify analytically the tradeoff between precoder word length and transmission rate degradation. More specifically, we prove a simple formula for the transmission-rate loss as a function of the number of bits used for precoding, the signal-to-noise ratio, and the standard line parameters. We demonstrate, through simulations on real lines, the accuracy of our estimates. Moreover, our results are stable in the presence of channel estimation errors. Lastly, we show how to use these estimates as a design tool for DSL linear crosstalk precoders. For example, we show that for standard VDSL2 precoded systems, 14 bit representation of the precoder entries results in capacity loss below 1% for lines over 300 m. View full abstract»

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  • Blind, Adaptive Channel Shortening Equalizer Algorithm Which Can Provide Shortened Channel State Information (BACS-SI)

    Page(s): 1483 - 1493
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (529 KB) |  | HTML iconHTML  

    Channel shortening equalization plays an important role in multicarrier modulation (MCM) systems. In this paper, we propose a blind channel shortening equalizer structure named blind, adaptive channel shortening equalizer which can provide the shortened channel state information (BACS-SI). The algorithm depends on the minimization of a cost function defined as the sum-squared difference of the autocorrelations of the shortened channel impulse response (CIR) and a target impulse response. The surface is proven to be multimodal; however, minima are shown to be related to each other in a certain way. A two-phase approach is proposed. In the first phase, the cost function is minimized by a stochastic gradient descent algorithm in order to find an arbitrary minimum. In the second phase using the relation between minima, genetic algorithms are employed to find the best minimum according to a fitness function. The algorithm can both successfully shorten the channel and also explicitly provides shortened CIR which is a necessary information for the proper operation of a MCM receiver, in contrast to many other algorithms proposed in the literature which cannot directly provide this information. View full abstract»

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  • Energy-Efficient Resource Allocation in Multipath CDMA Channels With Band-Limited Waveforms

    Page(s): 1494 - 1510
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1655 KB) |  | HTML iconHTML  

    This paper is focused on the cross-layer design problem of joint multiuser detection and power control for energy-efficiency optimization in wireless data networks through a game-theoretic approach. Unlike previous studies in this area, which have considered the application of game theory to achieve energy-efficiency in idealized synchronous code division multiple access systems, more realistic assumptions including system asynchronism, the use of band-limited chip-pulses, and the multipath distortion induced by the wireless channel are explicitly incorporated in the development of this paper. Several noncooperative games are proposed wherein each user may vary its transmit power and uplink receiver in order to maximize its utility, which is defined here as the ratio of data throughput to transmit power. In particular, the case in which a linear multiuser detector is adopted at the receiver is considered first, and then, the more challenging case in which a nonlinear decision feedback multiuser detector is employed is considered. Via large system analysis (LSA), a decentralized implementation of the power allocation game requiring very little prior information on the interference background is proposed. LSA is also used to compare the energy efficiency of several linear multiuser detectors, and to obtain the optimal (i.e., utility-maximizing) length of the training sequence of each data frame. Numerical results show the effectiveness of the proposed solutions, as well as a very satisfactory agreement of the LSA-based analysis with simulation results obtained for systems with finite (and not so large) numbers of users. View full abstract»

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  • Large-System-Based Performance Analysis and Design of Multiuser Cooperative Networks

    Page(s): 1511 - 1525
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (682 KB) |  | HTML iconHTML  

    In this paper, the performance of the cooperative multiuser direct-sequence code-division multiple-access (DS-CDMA) system is analyzed in the asymptotic regime where both the spreading codes and the number of users grow unboundedly large with the same ratio. Assuming that each terminal is paired with another user which, in addition to transmitting its own data, estimates and relay the information transmitted from its partner, a simple approximate signal-to-interference-plus-noise ratio (SINR) expression is derived that is independent from the spreading codes and explicitly accounts for the effects of the multiple-access interference (MAI) and the relay noise. The so-obtained SINR expression is then computed based entirely on the available local information and without any knowledge about the interfering users. The results obtained above are then used to optimally design the cooperative system. In particular, it is shown how the amount of cooperation between each collaborating pair can be adjusted to simultaneously achieve a preassigned target SINR for both users. Based on the local information, the globally optimal amount of the relay power is obtained that maximizes the achieved SINR at the access point. It is shown that increasing the relay power does not necessarily result in improving the quality of reception at the access point and, to maximize each user's SINR, its relay power should be carefully adjusted based on the environmental parameters such as the interpartner channel link and the powers of MAI and the relay noise. The connection between the cooperative and the conventional multiuser systems is also studied and simulations are used to demonstrate the validity of the analytical results. View full abstract»

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Aims & Scope

IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Zhi-Quan (Tom) Luo
University of Minnesota