By Topic

Signal Processing, IEEE Transactions on

Issue 5  Part 2 • Date May 2007

Filter Results

Displaying Results 1 - 25 of 41
  • Table of contents

    Publication Year: 2007 , Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (48 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Signal Processing publication information

    Publication Year: 2007 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (36 KB)  
    Freely Available from IEEE
  • Performance Analysis of Iterative Channel Estimation and Multiuser Detection in Multipath DS-CDMA Channels

    Publication Year: 2007 , Page(s): 1981 - 1993
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (681 KB) |  | HTML iconHTML  

    This paper examines the performance of decision-feedback-based iterative channel estimation and multiuser detection in channel coded aperiodic direct sequence code division multiple-access systems operating over multipath fading channels. First, explicit expressions describing the performance of channel estimation and parallel interference-cancellation-based multiuser detection are developed. These results are then combined to characterize the evolution of the performance of a system that iterates among channel estimation, multiuser detection and channel decoding. Sufficient conditions for convergence of this system to a unique fixed point are developed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Offline and Real-Time Methods for ML-PDA Track Validation

    Publication Year: 2007 , Page(s): 1994 - 2006
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (773 KB) |  | HTML iconHTML  

    We present two procedures for validating track estimates obtained using the maximum-likelihood probabilistic data association (ML-PDA) algorithm. The ML-PDA, developed for very low observable (VLO) target tracking, always provides a track estimate that must then be tested for target existence by comparing the value of the log likelihood ratio (LLR) at the track estimate to a threshold. Using extreme value theory, we show that in the absence of a target the LLR at the track estimate obeys approximately a Gumbel distribution rather than the Gaussian distribution previously ascribed to it in the literature. The offline track validation procedure relies on extensive offline simulations to obtain a set of track validation thresholds that are then used by the tracking system. The real-time procedure uses the data set that produced the track estimate to also determine the track validation threshold. The performance of these two procedures is investigated through simulation of two active sonar tracking scenarios by comparing the false and true track acceptance probabilities. These techniques have potential for use in a broader class of maximum likelihood estimation problems with similar structure View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Signal-Selective DOA Tracking for Wideband Cyclostationary Sources

    Publication Year: 2007 , Page(s): 2007 - 2015
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (462 KB) |  | HTML iconHTML  

    In this paper, a new signal-selective direction-of-arrival (DOA) tracking algorithm is presented for moving sources emitting narrowband or wideband cyclostationary signals. In this algorithm, DOAs of the sources are updated recursively based on the most current array output in a way that no data association is needed. Furthermore, by exploiting cyclostationarity, interference and noise are suppressed. Thus, only sources of interest are tracked. It is also shown that via a Kalman filter, tracking performance of this algorithm could be further improved. The effectiveness of the proposed algorithm is demonstrated by simulations View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Weiss–Weinstein Lower Bounds for Markovian Systems. Part 1: Theory

    Publication Year: 2007 , Page(s): 2016 - 2030
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (491 KB) |  | HTML iconHTML  

    Being essentially free from regularity conditions, the Weiss-Weinstein estimation error lower bound can be applied to a larger class of systems than the well-known Crameacuter-Rao lower bound. Thus, this bound is of special interest in applications involving hybrid systems, i.e., systems with both continuously and discretely distributed parameters, which can represent, in practice, fault-prone systems. However, the requirement to know explicitly the joint distribution of the estimated parameters with all the measurements makes the application of the Weiss-Weinstein lower bound to Markovian dynamic systems cumbersome. A sequential algorithm for the computation of the Crameacuter-Rao lower bound for such systems has been recently reported in the literature. Along with the marginal state distribution, the algorithm makes use of the transitional distribution of the Markovian state process and the distribution of the measurements at each time step conditioned on the appropriate states, both easily obtainable from the system equations. A similar technique is employed herein to develop sequential Weiss-Weinstein lower bounds for a class of Markovian dynamic systems. In particular, it is shown that in systems satisfying the Crameacuter-Rao lower bound regularity conditions, the sequential Weiss-Weinstein lower bound derived herein reduces, for a judicious choice of its parameters, to the sequential Crameacuter-Rao lower bound View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Weiss–Weinstein Lower Bounds for Markovian Systems. Part 2: Applications to Fault-Tolerant Filtering

    Publication Year: 2007 , Page(s): 2031 - 2042
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (510 KB) |  | HTML iconHTML  

    Characterized by sudden structural changes, fault-prone systems are modeled using the framework of systems with switching parameters or hybrid systems. Since a closed-form mean-square optimal filtering algorithm for this class of systems does not exist, it is of particular interest to derive a lower bound on the state estimation error covariance. The well known Crameacuter-Rao bound is not applicable to fault-prone systems because of the discrete distribution of the fault indicators, which violates the regularity conditions associated with this bound. On the other hand, the Weiss-Weinstein lower bound is essentially free from regularity conditions. Moreover, a sequential version of the Weiss-Weinstein bound, suitable for Markovian dynamic systems, is presented by the authors in a companion paper. In the present paper, this sequential version is applied to several classes of fault-prone dynamic systems. The resulting bounds can be used to examine fault detectability and identifiability in these systems. Moreover, it is shown that several recently reported lower bounds for fault-prone systems are special cases of, or closely related to, the sequential version of the Weiss-Weinstein lower bound View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Estimation of the Sinusoidal Signal Frequency Based on the Marginal Median DFT

    Publication Year: 2007 , Page(s): 2043 - 2051
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (418 KB) |  | HTML iconHTML  

    The marginal-median discrete Fourier transform (DFT) is used for estimation of complex sinusoidal signals embedded in an impulse noise environment. Expression for the marginal-median DFT of the sinusoidal signal in the neighborhood of the exact frequency is derived. Two specific displacement techniques are proposed in order to achieve an accurate estimation of frequency displaced from the frequency grid. They are based on specific ratio of the marginal-median DFT magnitudes for samples in the neighborhood of the marginal-median DFT maximum calculated over the frequency grid. Efficiency and accuracy of the proposed techniques is proved for mixed Gaussian and impulse noise environment View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Factor-Graph Algorithms for Equalization

    Publication Year: 2007 , Page(s): 2052 - 2065
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (670 KB) |  | HTML iconHTML  

    In this paper, we use the factor-graph framework to describe the statistical relationships that arise in the equalization of data transmitted over an intersymbol interference channel, and use it to develop several new algorithms for linear and decision feedback approaches. Specifically, we examine both unconstrained and constrained linear equalization and decision feedback equalization of a sequence of nonidentically distributed symbols that are transmitted over a linear, possibly time-varying, finite-length channel and then corrupted by additive white noise. Factor graphs are used to derive algorithms for each of these equalization tasks, including fast implementations. One important application of these algorithms is linear turbo equalization, which requires a linear equalizer that can process observations of nonidentically distributed transmitted symbols. We show how the output of these factor-graph-based algorithms can be used in an efficient implementation of a linear turbo equalizer View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Discrete Time-Frequency Characterizations of Dispersive Linear Time-Varying Systems

    Publication Year: 2007 , Page(s): 2066 - 2076
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (831 KB) |  | HTML iconHTML  

    A class of linear time-varying systems can be characterized by dispersive signal transformations, such as nonlinear shifts in the phase of the propagating signal, causing different frequencies to be shifted in time by different amounts. In this paper, we propose a discrete time-frequency model to decompose the dispersive system output into discrete dispersive frequency shifts and generalized time shifts, weighted by a smoothed and sampled version of the dispersive spreading function. The discretization formulation is obtained from the discrete narrowband system model through a unitary warping relation between the narrowband and dispersive spreading functions. This warping relation depends on the nonlinear phase transformations induced by the dispersive system. In order to demonstrate the effectiveness of the proposed discrete characterization, we investigate acoustic transmission over shallow water environments that suffers from severe degradations as a result of modal frequency dispersions and multipath fading. Using numerical results, we demonstrate that the discrete dispersive model can lead to a joint multipath-dispersion diversity that we achieve by properly designing the transmitted waveform and the reception scheme to match the dispersive environment characteristics View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Exact Convergence Analysis of Adaptive Filter Algorithms Without the Persistently Exciting Condition

    Publication Year: 2007 , Page(s): 2077 - 2083
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (473 KB) |  | HTML iconHTML  

    Exact convergence analysis of the recursive least square and least mean square (LMS) algorithms in adaptive filtering is presented for the case of sinusoidal signal cancellation without the persistently exciting condition. This situation occurs when the number of tap coefficients of the adaptive filter exceeds that of the complex sinusoids in the input signal. The convergent point of both algorithms is shown to be the one determined by the pseudo inverse of the deterministic covariance matrix. The convergence proof for the LMS algorithm is based on the Lyapunov function method. Finally, the validity of the obtained results is supported by simulation results View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Statistical Analysis of the LMS Algorithm Applied to Super-Resolution Image Reconstruction

    Publication Year: 2007 , Page(s): 2084 - 2095
    Cited by:  Papers (3)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1373 KB) |  | HTML iconHTML  

    Super resolution reconstruction of image sequences is highly dependent on quality of the motion estimation between successive frames. This work presents a statistical analysis of the least mean square (LMS) algorithm applied to super resolution reconstruction of an image sequence with translational global motion. Deterministic recursions are derived for the mean and mean square behaviors of the reconstruction error as functions of the registration errors. The new model describes the behavior of the algorithm in realistic situations, and significantly improves the accuracy of a simple model available in the literature. Monte Carlo simulations show very good agreement between actual and predicted behaviors View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Variable Explicit Regularization in Affine Projection Algorithm: Robustness Issues and Optimal Choice

    Publication Year: 2007 , Page(s): 2096 - 2109
    Cited by:  Papers (27)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (882 KB) |  | HTML iconHTML  

    A variable regularized affine projection algorithm (VR-APA) is introduced, without requiring the classical step size. Its use is supported from different points of view. First, it has the property of being Hinfin optimal and it satisfies certain error energy bounds. Second, the time-varying regularization parameter is obtained by maximizing the speed of convergence of the algorithm. Although we first derive the VR-APA for a linear time invariant (LTI) system, we show that the same expression holds if we consider a time-varying system following a first-order Markov model. We also find expressions for the power of the steady-state error vector for the VR-APA and the standard APA with no regularization parameter. Particularly, we obtain quite different results with and without using the independence assumption between the a priori error vector and the measurement noise vector. Simulation results are presented to test the performance of the proposed algorithm and to compare it with other schemes under different situations. An important conclusion is that the former independence assumption can lead to very inaccurate steady-state results, especially when high values of the projection order are used View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Low-Delay Nonuniform Pseudo-QMF Banks With Application to Speech Enhancement

    Publication Year: 2007 , Page(s): 2110 - 2121
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (716 KB) |  | HTML iconHTML  

    This paper presents a method for designing low-delay nonuniform pseudo quadrature mirror filter (QMF) banks. This method is motivated by the work of Li, Nguyen, and Tantaratana, in which the nonuniform filter bank is realized by combining an appropriate number of adjacent sub-bands of a uniform pseudo-QMF bank. In prior work, the prototype filter of the uniform pseudo-QMF bank was constrained to have linear phase and the overall delay associated with the filter bank was often unacceptably large for filter banks with a large number of sub-bands. This paper proposes a pseudo-QMF filter bank design technique that significantly reduces the delay by relaxing the linear phase constraints. An example in which an oversampled critical-band nonuniform filter bank is designed and applied to a two-state modeling speech enhancement system is presented in this paper. Comparison of the performance of this system to competing methods employing tree-structured, linear phase multiresolution analysis indicates that the approach described in this paper strikes a good balance between system performance and low delay View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Roundoff Noise Analysis of Signals Represented Using Signed Power-of-Two Terms

    Publication Year: 2007 , Page(s): 2122 - 2135
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (935 KB) |  | HTML iconHTML  

    It is a well-known fact that the multiplication of a number by an integer power-of-two is a very simple process in binary arithmetic. Hence, digital filters whose coefficient values are integer power-of-two are essentially multiplierless. The design of digital filters with power-of-two coefficient values require time-consuming optimization process and may not always be possible in some applications such as in adaptive filtering. Since hardware circuitry for real-time conversion of a binary integer into a sum of a limited number of signed power-of-two (SPT) terms is available, if the signal is expressed in SPT terms, i.e., in digit code, the filter is also multiplierless even though the coefficient values are not SPT. When each signal data is rounded to a limited number of SPT terms, a roundoff noise representing the roundoff error is introduced. In the SPT space, the quantization step size is nonuniform and so the roundoff noise characteristic is different from that produced when the quantization step size is uniform. This paper presents an analysis for the roundoff noise of signal represented using a limited number of SPT terms. The result is useful for determining the number of SPT terms required to represent a signal subject to a given roundoff noise View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On the Approximation of L_{2} Inner Products From Sampled Data

    Publication Year: 2007 , Page(s): 2136 - 2144
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1045 KB) |  | HTML iconHTML  

    Most signal processing applications are based on discrete-time signals although the origin of many sources of information is analog. In this paper, we consider the task of signal representation by a set of functions. Focusing on the representation coefficients of the original continuous-time signal, the question considered herein is to what extent the sampling process keeps algebraic relations, such as inner product, intact. By interpreting the sampling process as a bounded operator, a vector-like interpretation for this approximation problem has been derived, giving rise to an optimal discrete approximation scheme different from the Riemann-type sum often used. The objective of this optimal scheme is in the min-max sense and no bandlimitedness constraints are imposed. Tight upper bounds on this optimal and the Riemann-type sum approximation schemes are then derived. We further consider the case of a finite number of samples and formulate a closed-form solution for such a case. The results of this work provide a tool for finding the optimal scheme for approximating an L2 inner product, and to determine the maximum potential representation error induced by the sampling process. The maximum representation error can also be determined for the Riemann-type sum approximation scheme. Examples of practical applications are given and discussed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Polyphase Representation of Multirate Nonlinear Filters and Its Applications

    Publication Year: 2007 , Page(s): 2145 - 2157
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (710 KB) |  | HTML iconHTML  

    This paper proposes a polyphase representation for nonlinear filters, especially for Volterra filters. To derive the new realizations the well-known linear polyphase theory is extended to the nonlinear case. Both the upsampling and downsampling cases are considered. As in the linear case (finite-impulse response filters), neither the input signal nor the Volterra kernels must fulfil constraints in order to be realized in polyphase form. The computational complexity can be reduced significantly because of two reasons. On the one hand, all operations are performed at the low sampling rate and, on the other hand, a new null identity allows to remove many coefficients in the polyphase representation. Furthermore, some applications involving a nonlinear filter, an upsampler, and/or a downsampler are discussed to demonstrate the utility of the new approach to multirate nonlinear signal processing View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An EVD Algorithm for Para-Hermitian Polynomial Matrices

    Publication Year: 2007 , Page(s): 2158 - 2169
    Cited by:  Papers (29)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (813 KB) |  | HTML iconHTML  

    An algorithm for computing the eigenvalue decomposition of a para-Hermitian polynomial matrix is described. This amounts to diagonalizing the polynomial matrix by means of a paraunitary "similarity" transformation. The algorithm makes use of "elementary paraunitary transformations" and constitutes a generalization of the classical Jacobi algorithm for conventional Hermitian matrix diagonalization. A proof of convergence is presented. The application to signal processing is highlighted in terms of strong decorrelation and multichannel data compaction. Some simulated results are presented to demonstrate the capability of the algorithm View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • {Q} -Learning Algorithms for Constrained Markov Decision Processes With Randomized Monotone Policies: Application to MIMO Transmission Control

    Publication Year: 2007 , Page(s): 2170 - 2181
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (831 KB) |  | HTML iconHTML  

    This paper presents novel Q-learning based stochastic control algorithms for rate and power control in V-BLAST transmission systems. The algorithms exploit the supermodularity and monotonic structure results derived in the companion paper. Rate and power control problem is posed as a stochastic optimization problem with the goal of minimizing the average transmission power under the constraint on the average delay that can be interpreted as the quality of service requirement of a given application. Standard Q-learning algorithm is modified to handle the constraints so that it can adaptively learn structured optimal policy for unknown channel/traffic statistics. We discuss the convergence of the proposed algorithms and explore their properties in simulations. To address the issue of unknown transmission costs in an unknown time-varying environment, we propose the variant of Q-learning algorithm in which power costs are estimated in online fashion, and we show that this algorithm converges to the optimal solution as long as the power cost estimates are asymptotically unbiased View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Globally Convergent Deflationary Instantaneous Blind Source Separation Algorithm for Digital Communication Signals

    Publication Year: 2007 , Page(s): 2182 - 2192
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1082 KB) |  | HTML iconHTML  

    Recently an instantaneous blind source separation (BSS) approach that exploits the bounded magnitude structure of digital communications signals has been introduced. In this paper, we introduce a deflationary adaptive algorithm based on this criterion and provide its convergence analysis. We show that the resulting algorithm is convergent to one of the globally optimal points that correspond to perfect separation. The simulation examples related to the separation of digital communication signals are provided to illustrate the convergence and the performance of the algorithm View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fundamental Limitations on the Number of Resolvable Emitters Using a Geolocation System

    Publication Year: 2007 , Page(s): 2193 - 2202
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (453 KB) |  | HTML iconHTML  

    We derive conditions for unique geolocation of multiple radio-frequency emitters using a general observation model. These conditions specify the maximum number of emitters that can be uniquely located by a geolocation system, often referred to as the resolution capacity (RC). Our derivations extend previously published results for geolocation based on angle-of-arrival (AOA) estimation. We show that with no prior information, the RC is upper bounded by the total number of antenna elements in the system, i.e., LM, where M is the number of elements in each array and L is the number of arrays. In contrast, the RC of geolocation based on AOA is upper bounded by M. In addition, if the signals are known to be uncorrelated, and the arrays are uniform and linear, the RC is upper bounded by (LM)2-L(M-1)2-1. However, more emitters can be resolved using different types of arrays. Our results lead to the inevitable conclusion that geolocation based on AOA is suboptimal, and new methods should be developed that can jointly exploit the information collected by all the antenna arrays View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Nonstationary Hidden Markov Models for Multiaspect Discriminative Feature Extraction From Radar Targets

    Publication Year: 2007 , Page(s): 2203 - 2214
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1079 KB) |  | HTML iconHTML  

    This paper presents a new scheme for radar target recognition, in which we fuse sequential radar echoes from multiple target-radar aspect angles. The nonstationary hidden Markov model (NSHMM) is employed to characterize the sequential information contained in multiaspect radar echoes. Features from echoes are extracted via the multirelax algorithm, and moments are used to reduce the extracted-feature dimensionality. The proposed NSHMM has many parameters and states to be estimated, so the Markov chain Monte Carlo sampling algorithm is adopted. Finally, this new scheme is demonstrated with experiments on inverse synthetic aperture radar data View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Evaluation of Transmit Diversity in MIMO-Radar Direction Finding

    Publication Year: 2007 , Page(s): 2215 - 2225
    Cited by:  Papers (76)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (902 KB) |  | HTML iconHTML  

    It has been recently shown that multiple-input multiple-output (MIMO) antenna systems have the potential to dramatically improve the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, the target's radar cross section (RCS) fluctuations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it provides measures to overcome those degradations or even utilizes the RCS fluctuations for new applications. This paper explores how transmit diversity can improve the direction finding performance of a radar utilizing an antenna array at the receiver. To harness diversity, the transmit antennas have to be widely separated, while for direction finding, the receive antennas have to be closely spaced. The analysis is carried out by evaluating several Cramer-Rao bounds for bearing estimation and the mean square error of the maximum likelihood estimate View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Pilot-Assisted Time-Varying Channel Estimation for OFDM Systems

    Publication Year: 2007 , Page(s): 2226 - 2238
    Cited by:  Papers (117)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1750 KB) |  | HTML iconHTML  

    In this paper, we deal with channel estimation for orthogonal frequency-division multiplexing (OFDM) systems. The channels are assumed to be time-varying (TV) and approximated by a basis expansion model (BEM). Due to the time-variation, the resulting channel matrix in the frequency domain is no longer diagonal, but approximately banded. Based on this observation, we propose novel channel estimators to combat both the noise and the out-of-band interference. In addition, the effect of a receiver window on channel estimation is also studied. Our claims are supported by simulation results, which are obtained considering Jakes' channels with fairly high Doppler spreads View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Generalized Signal Richness Preservation Problem and Vandermonde-Form Preserving Matrices

    Publication Year: 2007 , Page(s): 2239 - 2250
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (562 KB) |  | HTML iconHTML  

    In this paper, a theoretical problem arising in digital communications, namely the generalized signal richness preservation problem, is addressed and studied. In order to solve the problem, a special class of square matrices, namely the "Vandermonde-form preserving" (VFP) matrices, is introduced and found to be highly relevant to the problem. Several properties of VFP matrices are studied in detail. The necessary and sufficient conditions of the problem have been found, and a systematic proof is also presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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
Sergios Theodoridis
University of Athens