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Signal Processing, IEEE Transactions on

Issue 10  Part 1 • Date Oct. 2004

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Displaying Results 1 - 25 of 35
  • Table of contents

    Publication Year: 2004 , Page(s): c1 - c4
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    Freely Available from IEEE
  • IEEE Transactions on Signal Processing publication information

    Publication Year: 2004 , Page(s): c2
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    Freely Available from IEEE
  • Indirectly estimated adaptive detectors for code-division multiple-access signals

    Publication Year: 2004 , Page(s): 2677 - 2689
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (632 KB) |  | HTML iconHTML  

    This paper presents the development of indirectly estimated adaptive (IDEA) detectors for code-division multiple-access (CDMA) signals in wireless communication systems. Multiuser CDMA detection is formulated as an inverse problem in the presence of noise, and the estimation of the detector parameters is accomplished using elements of regularization theory. The development of autonomous CDMA detectors that are capable of adjusting to the channel characteristics with the support of training sequences relies on data-dependent procedures designed to reduce the effect of noise and interfering users on the performance of the detector. The detector parameters can be computed by adaptive algorithms that require no matrix inversion. The proposed IDEA detector is evaluated and compared with existing multiuser CDMA detectors in terms of their robustness to noise, resistance to the near-far problem, and ability to handle multipath signals. View full abstract»

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  • Fast algorithms for mutual information based independent component analysis

    Publication Year: 2004 , Page(s): 2690 - 2700
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    This paper provides fast algorithms to perform independent component analysis based on the mutual information criterion. The main ingredient is the binning technique and the use of cardinal splines, which allows the fast computation of the density estimator over a regular grid. Using a discretized form of the entropy, the criterion can be evaluated quickly together with its gradient, which can be expressed in terms of the score functions. Both offline and online separation algorithms have been developed. Our density, entropy, and score estimators also have their own interest. View full abstract»

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  • Model enforcement: a unified feature transformation framework for classification and recognition

    Publication Year: 2004 , Page(s): 2701 - 2710
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB) |  | HTML iconHTML  

    Bayesian classifiers rely on models of the a priori and class-conditional feature distributions; the classifier is trained by optimizing these models to best represent features observed in a training corpus according to certain criterion. In many problems of interest, the true class-conditional feature probability density function (PDF) is not a member of the set of PDFs the classifier can represent. Previous research has shown that the effect of this problem may be reduced either by improving the models or by transforming the features used in the classifier. This paper addresses this model mismatch problem in statistical identification, classification, and recognition systems. We formulate the problem as the problem of minimizing the relative entropy, which is also known as the Kullback-Leibler distance, between the true conditional PDF and the hypothesized probabilistic model. Based on this formulation, we provide a computationally efficient solution to the problem based on volume-preserving maps; existing linear transform designs are shown to be special cases of the proposed solution. Using this result, we propose the symplectic maximum likelihood transform (SMLT), which is a nonlinear volume-preserving extension of the maximum likelihood linear transform (MLLT). This approach has many applications in statistical modeling, classification, and recognition. We apply it to the maximum likelihood estimation (MLE) of the joint PDF of order statistics and show a significant increase in the likelihood for the same number of parameters. We provide also phoneme recognition experiments that show recognition accuracy improvement compared with using the baseline Mel-Frequency Cepstrum Coefficient (MFCC) features or using MLLT. We present an iterative algorithm to jointly estimate the parameters of the symplectic map and the probabilistic model for both applications. View full abstract»

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  • Array interpolation and bias reduction

    Publication Year: 2004 , Page(s): 2711 - 2720
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB) |  | HTML iconHTML  

    Interpolation (mapping) of data from a given antenna array onto the output of a virtual array of more suitable configuration is well known in array signal processing. This operation allows arrays of any geometry to be used with fast direction-of-arrival (DOA) estimators designed for linear arrays. Conditions for preserving DOA error variance under such mappings have been derived by several authors. However, in many cases, such as omnidirectional signal surveillance over multiple octaves, systematic mapping errors will dominate over noise effects and cause significant bias in the DOA estimates. To prevent mapping errors from unduly affecting the DOA estimates, this paper uses a geometrical interpretation of a Taylor series expansion of the DOA estimator criterion function to derive an alternative design of the mapping matrix. Verifying simulations show significant bias reduction in the DOA estimates compared with previous designs. The key feature of the proposed design is that it takes into account the orthogonality between the manifold mapping errors and certain gradients of the estimator criterion function. With the new design, mapping of narrowband signals between dissimilar array geometries over wide sectors and large frequency ranges becomes feasible. View full abstract»

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  • Selection of a time-varying quadratic Volterra model using a wavelet packet basis expansion

    Publication Year: 2004 , Page(s): 2721 - 2728
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    We consider the identification of a time-varying nonlinear system based on a single realization of the system input-output. To enable identification, the system's time variation is approximated by a weighted sum of known basis sequences. Using wavelet packet basis sequences increases the flexibility of the model, allowing a suitable basis to be selected. A basis selection procedure is formulated using the Best Basis algorithm to choose the minimum entropy wavelet packet basis. The statistical significance of each of the chosen basis sequences is then tested using a multiple hypothesis testing procedure. Selecting individual sequences in this way achieves a specified level of confidence that the final model contains only those sequences that are significant. As an alternative, we also propose a search procedure, based on an information theoretic criterion, to select basis sequences. View full abstract»

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  • A fast recursive total least squares algorithm for adaptive FIR filtering

    Publication Year: 2004 , Page(s): 2729 - 2737
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (392 KB) |  | HTML iconHTML  

    This paper proposes a new fast recursive total least squares (N-RTLS) algorithm to recursively compute the TLS solution for adaptive finite impulse response (FIR) filtering. The N-RTLS algorithm is based on the minimization of the constrained Rayleigh quotient (c-RQ) in which the last entry of the parameter vector is constrained to the negative one. As analysis results on the convergence of the proposed algorithm, we study the properties of the stationary points of the c-RQ. The high computational efficiency of the new algorithm depends on the efficient computation of the fast gain vector (FGV) and the adaptation of the c-RQ. Since the last entry of the parameter vector in the c-RQ has been fixed as the negative one, a minimum point of the c-RQ is searched only along the input data vector, and a more efficient N-RTLS algorithm is obtained by using the FGV. As compared with Davila's RTLS algorithms, the N-RTLS algorithm saves the 6M number of multiplies, divides, and square roots (MADs). The global convergence of the new algorithm is studied by LaSalle's invariance principle. The performances of the relevant algorithms are compared via simulations, and the long-term numerical stability of the N-RTLS algorithm is verified. View full abstract»

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  • Blind equalization of frequency-selective channels by sequential importance sampling

    Publication Year: 2004 , Page(s): 2738 - 2748
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB) |  | HTML iconHTML  

    This paper introduces a novel blind equalization algorithm for frequency-selective channels based on a Bayesian formulation of the problem and the sequential importance sampling (SIS) technique. SIS methods rely on building a Monte Carlo (MC) representation of the probability distribution of interest that consists of a set of samples (usually called particles) and associated weights computed recursively in time. We elaborate on this principle to derive blind sequential algorithms that perform maximum a posteriori (MAP) symbol detection without explicit estimation of the channel parameters. In particular, we start with a basic algorithm that only requires the a priori knowledge of the model order of the channel, but we subsequently relax this assumption and investigate novel procedures to handle model order uncertainty as well. The bit error rate (BER) performance of the proposed Bayesian equalizers is evaluated and compared with that of other equalizers through computer simulations. View full abstract»

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  • Blind identification of SIMO systems and simultaneous estimation of multiple time delays from HOS-based inverse filter criteria

    Publication Year: 2004 , Page(s): 2749 - 2761
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    Higher order statistics-based inverse filter criteria (IFC) have been effectively used for blind equalization of single-input multiple-output (SIMO) systems. Recently, Chi and Chen reported a relationship between the unknown SIMO system and the optimum equalizer designed by the IFC for finite signal-to-noise ratio (SNR). In this paper, based on this relationship, an iterative fast Fourier transform (FFT)-based nonparametric blind system identification (BSI) algorithm and an FFT-based multiple-time-delay estimation (MTDE) algorithm are proposed with a given set of non-Gaussian measurements. The proposed BSI algorithm allows the unknown SIMO system to have common subchannel zeros, and its performance (estimation accuracy) is superior to that of the conventional IFC-based methods. The proposed MTDE algorithm can simultaneously estimate all the (P-1) time delays (with respect to a reference sensor) with space diversity of sensors exploited; therefore, its performance (estimation accuracy) is robust to the nonuniform distribution of SNRs of P ≥ 2 sensors (due to channel fading). Some simulation results are presented to support the efficacy of the proposed BSI algorithm and MTDE algorithm. View full abstract»

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  • Time-domain oversampled lapped transforms: theory, structure, and application in image coding

    Publication Year: 2004 , Page(s): 2762 - 2775
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1344 KB) |  | HTML iconHTML  

    This paper generalizes time-domain lapped transforms (TDLTs) proposed by Tran et al. to oversampled systems, thus leading to time-domain oversampled lapped transforms (TDOLTs). These new transforms correspond to a subclass of oversampled linear-phase perfect reconstruction filterbanks (OLPPRFBs), which can be implemented by adding a prefilter before the discrete cosine transform (DCT) and a post-filter after the inverse discrete cosine transform (IDCT). Structures of the pre- and post-filters are developed, and the frame-theoretic properties of TDOLTs are analyzed. A new parameterization of lattice matrices through the Givens-QR factorization is proposed for unconstrained optimization. Comparisons with other parameterization methods are also included. Several design examples, along with some image coding results, are presented to demonstrate the validity of the theory and the potential of TDOLTs in image coding, especially in error-resilient coding. View full abstract»

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  • Weighted median filters admitting complex-valued weights and their optimization

    Publication Year: 2004 , Page(s): 2776 - 2787
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (680 KB) |  | HTML iconHTML  

    This paper introduces the concept of complex weighted median (WM) filtering admitting complex weighting. Unlike previous approaches in the literature that only allowed positive real-valued weights, the new WM structures exhibit improved performance as they exploit the richness of unrestricted complex weighting. To this end, the newly defined complex WM structures synthesize filtering operations, whereas the prior structures could only attain smoothing properties due to the inherent constraints imposed on the weights. In order to overcome the two-dimensional (2-D) search burden associated with the computation of the complex WM, two fast, robust, and very efficient approximations are introduced. Adaptive optimization algorithms for their design are developed leading to simple LMS-type weight updates. Several simulations are shown illustrating the performance of the new complex WM filter structures. View full abstract»

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  • Orthogonal polynomials for complex Gaussian processes

    Publication Year: 2004 , Page(s): 2788 - 2797
    Cited by:  Papers (30)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (504 KB) |  | HTML iconHTML  

    Power amplifiers are the major source of nonlinearity in communications systems. Such nonlinearity causes spectral regrowth as well as in-band distortion, which leads to adjacent channel interference and increased bit error rate. Polynomials are often used to model the nonlinear power amplifier or its predistortion linearizer. In this paper, we present a novel set of orthogonal polynomials for baseband Gaussian input to replace the conventional polynomials and show how they alleviate the numerical instability problem associated with the conventional polynomials. The orthogonal polynomials also provide an intuitive means of spectral regrowth analysis. View full abstract»

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  • An improved training algorithm for nonlinear kernel discriminants

    Publication Year: 2004 , Page(s): 2798 - 2806
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (504 KB) |  | HTML iconHTML  

    A simple method to derive nonlinear discriminants is to map the samples into a high-dimensional feature space F using a nonlinear function and then to perform a linear discriminant analysis in F. Clearly, if F is a very high, or even infinitely, dimensional space, designing such a receiver may be a computationally intractable problem. However, using Mercer kernels, this problem can be solved without explicitly mapping the data to F. Recently, a powerful method of obtaining nonlinear kernel Fisher discriminants (KFDs) has been proposed, and very promising results were reported when compared with the other state-of-the-art classification techniques. In this paper, we present an extension of the KFD method that is also based on Mercer kernels. Our approach, which is called the nonlinear kernel second-order discriminant (KSOD), consists of determining a nonlinear receiver via optimization of a general form of second-order measures of performance. We also propose a complexity control procedure in order to improve the performance of these classifiers when few training data are available. Finally, simulations compare our approach with the KFD method. View full abstract»

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  • Efficient wideband channelizer for software radio systems using modulated PR filterbanks

    Publication Year: 2004 , Page(s): 2807 - 2820
    Cited by:  Papers (32)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    An efficient method is proposed for channelizing frequency division multiplexed (FDM) channels in wideband software radio (SWR) received signals that do not satisfy the conditions required for polyphase decomposition of the discrete filterbank (DFB) channelizer. The proposed method, which uses modulated perfect reconstruction (PR) filterbanks, requires fewer computations than DFBs for channelizing wideband signals that are composed of FDM channels of nonequal bandwidths, especially when a large number of channels are extracted. The proposed channelizer, if applied in the reverse direction, can be used to synthesize a set of channels with nonequal bandwidths into a single wideband signal in SWR transmitters. A method is also proposed for efficiently designing the modulated PR filterbanks, which have a large number of subchannels and prototype filters with high stopband attenuations that are used in the proposed channelizer. The computational complexity of the proposed channelizer is compared with the complexity of the DFB channelizer for channelizing the wideband and high-dynamic-range signals that are typical of SWR systems, and simulation results of the proposed channelization method are discussed. View full abstract»

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  • Blind multiantenna receivers for dispersive DS/CDMA channels with no channel-state information

    Publication Year: 2004 , Page(s): 2821 - 2835
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    The problem of blind multiuser detection for a direct sequence code division multiple access (DS/CDMA) system employing multiple transmit and receive antennae over a fading dispersive channel is considered. Relying upon a well-known signal representation, the strategy of two-stage multiuser detection is extended to the multiantenna case. Several design criteria are considered for both interference suppression and integration of the signals available at each antenna. In all cases, substantial immunity to multiple access interference (MAI) and intersymbol interference (ISI) is achieved, with no prior information as to the channel state and as to the number and the signatures of the interfering users. Interestingly, the newly proposed strategy, while being practically equivalent to existing competitors for low users' number, proves much more effective as the network load increases. Additionally, a closed-form formula for the bit-error-rate and a lower bound to the near-far resistance are derived for uncoded systems and subsequently extended to space-time coded systems, showing that these analytical results apply not only to the system under consideration but also to any linear receiver performing differential detection. View full abstract»

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  • Existence of codes with constant PMEPR and related design

    Publication Year: 2004 , Page(s): 2836 - 2846
    Cited by:  Papers (25)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (440 KB) |  | HTML iconHTML  

    Recently, several coding methods have been proposed to reduce the high peak-to-mean envelope ratio (PMEPR) of multicarrier signals. It has also been shown that with probability one, the PMEPR of any random codeword chosen from a symmetric quadrature amplitude modulation/phase shift keying (QAM/PSK) constellation is logn for large n, where n is the number of subcarriers. Therefore, the question is how much reduction beyond logn can one asymptotically achieve with coding, and what is the price in terms of the rate loss? In this paper, by optimally choosing the sign of each subcarrier, we prove the existence of q-ary codes of constant PMEPR for sufficiently large n and with a rate loss of at most logq2. We also obtain a Varsharmov-Gilbert-type upper bound on the rate of a code, given its minimum Hamming distance with constant PMEPR, for large n. Since ours is an existence result, we also study the problem of designing signs for PMEPR reduction. Motivated by a derandomization algorithm suggested by Spencer, we propose a deterministic and efficient algorithm to design signs such that the PMEPR of the resulting codeword is less than clogn for any n, where c is a constant independent of n. For symmetric q-ary constellations, this algorithm constructs a code with rate 1-logq2 and with PMEPR of clogn with simple encoding and decoding. Simulation results for our algorithm are presented. View full abstract»

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  • Non data-aided estimation of the modulation index of continuous phase modulations

    Publication Year: 2004 , Page(s): 2847 - 2861
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB)  

    In this paper, a new non data-aided estimator of the modulation index of continuous phase modulated (CPM) signals is proposed. It is based on the observation that the inverse of the index is the smallest positive real number a CPM signal should be raised to in order to generate a sinusoid of period 2T, where T is the symbol period. The asymptotic behavior of the estimator is studied. If N is the sample size, the estimation error is shown to converge to a non-Gaussian distribution at a rate of 1/N. Simulation results sustain the conclusions of the theoretical asymptotic analysis. View full abstract»

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  • Semidefinite relaxation based multiuser detection for M-ary PSK multiuser systems

    Publication Year: 2004 , Page(s): 2862 - 2872
    Cited by:  Papers (47)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    Because of the powerful symbol error performance of multiuser maximum-likelihood (ML) detection, recently, there has been much interest in seeking effective ways of approximating multiuser ML detection (MLD) with affordable computational costs. It has been illustrated that for the synchronous code division multiple access (CDMA) scenario, the so-called semidefinite relaxation (SDR) algorithm can accurately and efficiently approximate multiuser MLD. This SDR-MLD algorithm, however, can only handle binary and quadratic phase shift keying (PSK) symbol constellations. In this sequel, we propose an extended SDR algorithm for MLD with M-ary PSK (MPSK) constellations. For the synchronous CDMA scenario, the proposed SDR algorithm provides an attractive polynomial-time complexity order of K3.5, where K is the number of users. Simulation results indicate that the proposed detector provides improved symbol error performance compared with several commonly used multiuser detectors. View full abstract»

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  • Effects of imperfect blind channel estimation on performance of linear CDMA receivers

    Publication Year: 2004 , Page(s): 2873 - 2884
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB) |  | HTML iconHTML  

    In a code division multiple access (CDMA) system, signal detection under multipath distortion typically requires estimation of unknown channel parameters first. In such a scenario, performance of receivers highly relies on the accuracy of channel estimates. In this paper, effects of channel estimation errors on the performance of linear CDMA receivers due to finite data samples are studied when channel parameters are estimated blindly by a recently proposed covariance-matching technique. Those receivers include zero-forcing (ZF), direct matrix-inversion (DMI) minimum mean-square-error (MMSE), subspace MMSE, and RAKE receivers. Their output signal-to-interference-plus-noise ratios (SINRs) and bit-error-rates (BERs) are adopted for performance measures. Expressions for performance indicators under such an imperfect condition are derived from a perturbation perspective and verified by simulation examples. View full abstract»

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  • Soft input channel estimation for turbo equalization

    Publication Year: 2004 , Page(s): 2885 - 2894
    Cited by:  Papers (55)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB) |  | HTML iconHTML  

    In this paper, we consider soft decision directed channel estimation for turbo equalization. To take advantage of soft information provided by the decoder, a minimum mean square error linear channel estimator is derived under an uncorrelated channel tap model, and a soft input recursive least squares algorithm is also developed by modifying the cost function of the conventional recursive least squares algorithm. The performance of the proposed channel estimators are analyzed in terms of mean square identification error (MSIE) for stationary channels. Simulation results for both time-invariant and time-varying frequency-selective Rayleigh fading channels are also presented. View full abstract»

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  • Asymptotic performance evaluation of space-frequency MMSE filters for OFDM

    Publication Year: 2004 , Page(s): 2895 - 2910
    Cited by:  Papers (3)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB) |  | HTML iconHTML  

    This paper proposes and analyzes two different linear space-frequency architectures for the reception of OFDM-modulated signals: the classical sample matrix inversion (SMI) algorithm and a new architecture that maximizes the output signal-to-interference-plus noise ratio (MSINR). The performance of these two linear receivers is compared in terms of asymptotic output SINR, taking into account the finite sample size effect through the asymptotic covariance of the filter weights. The analysis is asymptotic in the sense that the performance is analyzed, assuming that both the number of carriers and the prefix length of the OFDM signal increase without bound at the same rate, whereas their quotient remains constant. Assuming that the carrier frequencies become asymptotically close to one another, we are able to derive explicit equations that shed some light on the influence of the frequency selectivity of channel and interference on the relative performance of the two approaches. The results are useful in the sense that they provide first-order approximations to the (asymptotically) optimum number of adjacent carriers to be processed by a single beamformer in a finite sample size situation. View full abstract»

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  • Performance and optimized design of space-time codes for MIMO wireless systems with imperfect channel estimates

    Publication Year: 2004 , Page(s): 2911 - 2923
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB) |  | HTML iconHTML  

    Multiple-antennas constitute an effective mean to achieve spatial diversity in emerging bandwidth-efficient multiple-input multiple-output (MIMO) wireless systems. Until now, most contributions in this area are focused on the two limit cases of fully coherent and fully incoherent decoding, which, in turn, occur when perfect channel estimates and no channel estimates are available at the receiver. However, very accurate channel estimates typically demand long training sequences that reduces spectral efficiency. Therefore, testing capabilities of multiple-antenna systems with partially coherent decoding may be appealing for improving power-versus-bandwidth tradeoff. In this contribution, we focus on the optimized design and performance evaluations of multiple-antenna block-coded systems with partially-coherent maximum-likelihood (ML) decoding. After considering emerging fourth-generation WLANs (4GWLANs) as a possible application scenario, we present new performance bounds and optimized design criteria together with a new family of robust space-time unitary block codes that "self-match" to channel-estimation errors. We name these codes "self matching.". View full abstract»

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  • A leaky RLS algorithm: its optimality and implementation

    Publication Year: 2004 , Page(s): 2924 - 2936
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB) |  | HTML iconHTML  

    A leaky recursive least squares (LRLS) algorithm obtained by a criterion of the ridge regression with the exponential weighting factor was recently proposed by one of the authors. On the other hand, an optimization criterion for improving the method of total least squares (TLS) has been proposed by Chandrasekaran et al. In this work, it is expressed that there is a case where the equation obtained by the criterion of the LRLS algorithm is identical to one obtained by the extended criterion of Chandrasekaran et al. In addition, some implementations of the LRLS filter by using the method for updating the eigendecomposition of rank-one matrix updates, or by using the leaky least mean square (LLMS) algorithm, are introduced to decrease the computational complexity of the LRLS algorithm. Moreover, by means of computer experiments, it is shown that the LRLS and the LLMS algorithms yield more precise estimation parameters than the RLS algorithm when the method of Chandrasekaran et al. is more useful than that of LS and TLS. Besides, it is demonstrated that the LLMS algorithm can be effectively introduced into a noise reduction system for noisy speech signals to support the theoretical results in this work. View full abstract»

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  • Sub-band adaptive filtering with delay compensation for active control

    Publication Year: 2004 , Page(s): 2932 - 2941
    Cited by:  Papers (9)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    This paper introduces a filtered-x least-mean-square (FXLMS) based sub-band adaptive algorithm with error path delay compensation. Our algorithm avoids the signal path delay while compensating for the error path delay, thus increasing system stability. Simulation results are presented to demonstrate experimentally the efficiency of this new adaptive algorithm. 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

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Meet Our Editors

Editor-in-Chief
Sergios Theodoridis
University of Athens