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Subspace blind adaptive detection for multiuser CDMA

IEEE TRANSACTIONS ON COMMUNICATIONS 2000年第1期48卷 169-175页

作者： Roy, S Univ Texas San Antonio San Antonio TX 78285 USA

Direct adaptive realizations of the linear minimum mean-square error (MMSE) receiver for direct-sequence code-division multiple access possess the attractive feature of not requiring any explicit information of interference parameters such as timing, amplitudes, or spreading sequences;however, they need a training sequence for the desired user. Recently, a new blind adaptive receiver was proposed based on an anchored least mean-squared (lms) algorithm that requires only the spreading code and symbol timing of the desired user but obviates the need for a training sequence, In this work, it is analytically demonstrated that the blind lms algorithm always provides (nominally) faster convergence than the training driven lms-MMSE receiver of but at the cost of increased tap-weight fluctuations or misadjustment. Second, the property that the optimal MMSE or minimum-output energy filter coefficients lies in the signal subspace is exploited to propose a new efficient blind adaptive receiver requiring fewer adaptive coefficients. Improved detector characteristics (superior convergence rates and steady-state signal-to-interference-plus-noise ratios) is indicated by analysis and supported by simulation.

关键词： blind adaptive filtering lms algorithm multiuser CDMA

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Frequency domain analysis of tracking and noise performance of adaptive algorithms

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1998年第5期46卷 1314-1332页

作者： Ninness, B Gomez, JC Univ Newcastle Dept Elect & Comp Engn CIDAC Callaghan NSW Australia

In this paper an analysis of the tracking and noise performance of several adaptive algorithms is carried ant for the case of model structures with fixed pale positions, Such structures have recently been proposed as an efficient generalization of the common FIR model structure. The focus of this work is to analyze the associated tradeoff between noise sensitivity and tracking ability in the frequency domain by illustrating how it is influenced by such things as input and noise spectral densities, step size, and-what is the main focus of this paper-the choice of the fixed pole locations, The latter influence is aot described by pre-existing analysis but is shown here to be amenable to attack bg a particular class of orthonormal bases.

关键词： adaptive filtering lms algorithm orthonormal bases recursive estimation

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Statistical-Mechanical Analysis of Adaptive Filter With Clipping Saturation-Type Nonlinearity

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2022年 70卷 4867-4882页

作者： Miyoshi, Seiji Kansai Univ Fac Engn Sci Dept Elect Elect & Informat Engn Suita Osaka 5648680 Japan

In most practical adaptive signal processing systems, e.g., active noise control, active vibration control, and acoustic echo cancellation, substantial nonlinearities that cannot be neglected exist. In this paper, we analyze the behaviors of an adaptive system in which the output of the adaptive filter has the clipping saturation-type nonlinearity by a statistical-mechanical method. We discuss the dynamical and steady-state behaviors of the adaptive system by performing asymptotic analysis, steady-state analysis, and numerical calculation. As a result, it is clarified that the saturation value has a critical point at which the system's mean-square stability and instability switch. The obtained theory well explains the strange behaviors around the critical point observed in the computer simulation. Finally, the exact value of the critical point is also derived.

关键词： Adaptive systems Behavioral sciences Signal processing algorithms Steady-state Analytical models Linearity Adaptive filters Adaptive filter adaptive signal processing system identification lms algorithm clipping saturation-type nonlinearity piecewise linearity statistical-mechanical analysis

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A new efficient two-channel backward algorithm for speech intelligibility enhancement: A subband approach

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APPLIED ACOUSTICS 2014年 76卷 209-222页

作者： Djendi, Mohamed Bendoumia, Redha Univ Saad Dahlab Blida Signal Proc & Image Lab LATSI Blida 09000 Algeria

This paper addresses the problem of speech intelligibility enhancement by adaptive filtering algorithms employed with subband techniques. The two structures named the forward and backward blind source separation structures are extensively used in the speech enhancement and source separation areas, and largely studied in the literature with convolutive and non-convolutive mixtures. These two structures use two-microphones to generate the convolutive/non-convolutive mixing signal, and provide at the outputs the target and the jammer signal components. In this paper, we focus our interest on the backward structure employed to enhance the speech signal from a convolutive mixture. Furthermore, we propose a subband implementation of this structure to improve its behavior with speech signal. The new proposed subband-Backward BSS (SBBSS) structure allows a very important improvement of the convergence speed of the adaptive filtering algorithms when the subband-number is selected high. In order to improve the robustness of the proposed subband structure, we have adapted then applied a new criterion that combines the System Mismatch and the Mean-Errors criterion minimization. The proposed subband backward structure, when it is combined with this new criterion minimization, allows to enhance the output speech signal by reducing the distortion and the noise components. The performance of the proposed subband backward structure is validated through several objective criteria which are given and described in this paper. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Backward structures lms algorithm Speech intelligibility Noise reduction Speech distortion Subband technique

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Multi-user receivers for a multiple-access system based on chaotic sequences on unknown asynchronous frequency-selective channels

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SIGNAL PROCESSING 2010年第2期90卷 587-598页

作者： Coulon, Martial Roviras, Diniel Univ Toulouse INPT ENSEEIHT IRIT Lab F-31071 Toulouse 7 France CNAM Paris LAETITIA Lab F-75003 Paris France

This article deals with the problem of multi-user detection for a chaos-based multiple-access system, using a Differential Chaos Shift Keying (DCSK) modulation. The transmission channels are frequency-selective (multipath), and the channel characteristics (gains and delays) are unknown at the receiver side. It is only assumed that estimates of the minimum and maximum delays are available, only for the channel corresponding to the user of interest. Under such assumptions, a least-mean-square detector is derived, whose theoretical performances are provided. This detector is compared with the detector obtained when the delays are known, and with the LMMSE detector, for which all system parameters are available. The theoretical analysis is confirmed by the simulation results, which show that the lms detector is not dramatically degraded with respect to the LMMSE detector, and that it is quite robust with respect to poor accuracy of the delay estimation. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Chaotic communications DCSK modulation Multiple-access Multi-user detection Adaptive filtering lms algorithm Multipath channels

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Performance analysis of an adaptive two-stage PICCDMA receiver in AWGN channels

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SIGNAL PROCESSING 2008年第6期88卷 1413-1427页

作者： Hsieh, Yu-Tao Wu, Wen-Rong Ind Technol Res Inst SoC Technol Ctr Hsinchu 310 Taiwan Natl Chiao Tung Univ Dept Commun Engn Hsinchu 300 Taiwan

Parallel interference cancellation (PIC) is considered a simple yet effective multiuser detector for direct-sequence code-division multiple-access (DS-CDMA) systems. However, its performance may deteriorate due to unreliable interference cancellation in the early stages. Thus, a partial PIC detector, in which partial cancellation factors (PCFs) are introduced to control the interference cancellation level, has been developed as a remedy. Recently, an interesting adaptive multistage PIC algorithm was proposed. In this scheme, coefficients combining the channel responses and optimal PCFs are blindly trained with the least mean square (lms) algorithm. The algorithm is simple to implement, inherently applicable to time-varying environments, and superior to the non-adaptive type of partial PICs. Despite its various advantages, its performance has not been theoretically analyzed yet. The contribution of this paper is to fill the gap by analyzing an adaptive two-stage PIC in AWGN channels. We explicitly derive the analytical results for optimal weights, weight-error means, and weight-error variances. Based on these results, we finally derive the output bit error rate (BER) for each user. Simulation results indicate that our analytical results highly agree with empirical ones. (c) 2008 Elsevier B.V. All rights reserved.

关键词： parallel interference cancellation performance analysis lms algorithm

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Recursive inverse algorithm: Mean-square-error analysis

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DIGITAL SIGNAL PROCESSING 2017年 66卷 10-17页

作者： Salman, Mohammad Shukri Kukrer, Osman Hocanin, Aykut Amer Univ Middle East Dept Elect Engn Kuwait Kuwait Eastern Mediterranean Univ Dept Elect & Elect Engn TR-10 Gazimagosa Mersin Turkey

The recently proposed recursive inverse (RI) adaptive algorithm has shown improved performance compared to some well-known adaptive algorithms [1]. However, there has been no detailed study of its performance. In this paper, we provide an analytical treatment of the ensemble-average learning curve of the RI algorithm. A novel analytical result which describes the learning behavior of the RI algorithm is obtained. It is shown that within limits of approximation, the excess mean-square-error (MSE) of the algorithm approaches zero and the RI algorithm converges to a lower steady-state MSE than the lms algorithm. The results show that the theoretical and experimental MSE curves of the RI algorithm are in agreement. Also, the MSE analysis of the RI algorithm in a nonstationary environment, where the optimum weight is assumed to be randomly changing about a fixed vector, is derived. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Mean-square-error Excess MSE lms algorithm RLS algorithm

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Alias-free subband adaptive filtering with critical sampling

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2008年第5期56卷 1894-1904页

作者： Kim, SangGyun Yoo, Chang D. Nguyen, Truong Q. Korea Adv Inst Sci & Technol Div Elect Engn Sch Elect Engn & Comp Sci Taejon 305701 South Korea Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

To overcome the limitations of a conventional fullband adaptive filtering, various subband adaptive filtering (SAF) structures have been proposed. Properly designed, an SAF will converge faster at a lower computational cost than a fullband structure. However, its design should consider the following two facts: the interband aliasing introduced by the downsampling process degrades its performance, and the filter bank in the SAF introduces additional computational overhead and system delay. In this paper, to fully exploit the benefits of using an SAF, an almost alias-free SAF structure with critical sampling is proposed. The interband alising is removed from the subband signal by isolating the aliasing using a bandwidth-increased analysis filter. Computer simulations show that the proposed structure converges faster than both an equivalent fullband structure at lower computational complexity and recently proposed SAF structures for a colored input.

关键词： adaptive filtering interband aliasing lms algorithm multirate signal processing subband adaptive filtering

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Adaptive noise reduction of InSAR images based on a complex-valued MRF model and its application to phase unwrapping problem

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2002年第3期40卷 699-709页

作者： Suksmono, AB Hirose, A Univ Tokyo RCAST Tokyo 1538904 Japan Univ Tokyo Dept Frontier Informat Tokyo 1538904 Japan

We propose a new adaptive noise reduction method for interferometric synthetic aperture radar (InSAR) complex-amplitude images. In the proposed method, we detect residues (singular points) in the phase image as well as their neighbors at first. Normal areas that contain no residue are used for the estimation of correct pixel values at the marked residues according to 5th order non-causal complex-valued Markov random field (CMRF) model. The process is performed block-wise with the assumption of a locally stationary condition of statistics. Using a CMRF lattice complex-valued neural-network, the error energy defined as the squared norm of distance between signal and estimated values is minimized by lms steepest descent algorithm. Eventually, the number of residues is decreased. An application is also presented. An InSAR image around NIL Fuji is processed by the proposed technique and then phase-unwrapped by the branch-cut method. It is found that after the application of the proposed method, a better phase unwrapped image can be obtained successfully.

关键词： branch-cut method complex-valued MRF complex-valued neural network interferometric synthetic aperture radar (InSAR) lms algorithm Markov random field neural network parameter estimation phase unwrapping phase noise filtering residue

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Convergence analysis of an online approach to parameter estimation problems based on binary observations

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AUTOMATICA 2012年第11期48卷 2837-2842页

作者： Jafari, Kian Juillard, Jerome Roger, Morgan SUPELEC Dept Signal Proc & Elect Syst Gif Sur Yvette France

In this paper, we present an online identification method to the problem of parameter estimation from binary observations. A recursive identification algorithm with low-storage requirements and computational complexity is derived. We prove the convergence of this method provided that the input signal satisfies a strong mixing property. Some simulation results are then given in order to illustrate the properties of this method under various scenarios. This method is appealing in the context of microelectronic devices since it only requires a 1-bit analog-to-digital converter, with low power consumption and minimal silicon area. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： System identification Parameter estimation Binary signals lms algorithm Convergence analysis

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