7,712 research outputs found

    Blind identification of FIR channels with multiple users via spatio-temporal processing

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    A new method is proposed for blind identification of possibly nonminimum phase FIR channels with multiple users. The technique exploits the structure of the signals received by an antenna array in both the temporal and spatial frequency domains. Although in the single antenna case it is necessary to use cyclostationary signals or higher order statistics to identify the magnitude and phase of the channel, the present authors circumvent such a requirement by exploiting certain multichannel features of the array. They show that if multiple users are present, the nonminimum phase channels associated with each user can still be identified from the second-order statistics, provided additional spatial structure exists

    Exact blind channel estimator

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    Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 43-45.Recently blind identification of single-input multiple-output (SIMO) FIR channels has received considerable attention. The obtained exact identification approaches place over-restrictive constraints on the channels. In this thesis least set of constraints on the channels are placed and the noise-free blind channel identification problem is solved in two stages: The identification of the uncommon zeros followed by the identification of the common zeros of the channels. The minimum number of samples required to identify the uncommon zeros is specified, and closed form solutions are obtained. Also a binary-tree algorithm is proposed for the computation of the uncommon zeros efficiently. Then the common zeros of the channels are identified by a novel pruning algorithm. Finally a simulation example is presented to illustrate these ideas.Ă–zdemir, Ahmet KemalM.S

    Identificación ciega de sistemas SIMO con señal de entrada dispersa

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    We consider the blind identification of FIR channels with a single input and multiple outputs when the input signal is sparse. The problem is equivalent to identifying the mixing matrix for underdetermined blind source separation, but with temporal correlation among the sources. The length of each channel is assumed known, or previously estimated. Exploiting the sparse character of the input signal, the algorithm solves sequentially the three identification problems: estimating the directions of each column of the channel matrix; estimating their Lâ‚‚-norm; and finding the most likely order of the columns. The performance of the algorithm in additive noise and its computational cost are compared against subspace-based techniques

    Structure-Based Subspace Method for Multi-Channel Blind System Identification

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    In this work, a novel subspace-based method for blind identification of multichannel finite impulse response (FIR) systems is presented. Here, we exploit directly the impeded Toeplitz channel structure in the signal linear model to build a quadratic form whose minimization leads to the desired channel estimation up to a scalar factor. This method can be extended to estimate any predefined linear structure, e.g. Hankel, that is usually encountered in linear systems. Simulation findings are provided to highlight the appealing advantages of the new structure-based subspace (SSS) method over the standard subspace (SS) method in certain adverse identification scenarii.Comment: 5 pages, Submitted to IEEE Signal Processing Letters, January 201

    Low Complexity Blind Equalization for OFDM Systems with General Constellations

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    This paper proposes a low-complexity algorithm for blind equalization of data in OFDM-based wireless systems with general constellations. The proposed algorithm is able to recover data even when the channel changes on a symbol-by-symbol basis, making it suitable for fast fading channels. The proposed algorithm does not require any statistical information of the channel and thus does not suffer from latency normally associated with blind methods. We also demonstrate how to reduce the complexity of the algorithm, which becomes especially low at high SNR. Specifically, we show that in the high SNR regime, the number of operations is of the order O(LN), where L is the cyclic prefix length and N is the total number of subcarriers. Simulation results confirm the favorable performance of our algorithm

    Multichannel receivers from ofdm and tdma in mobile communications

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    This paper addresses the use of multichannel receivers for blind equalization in TDMA under frequency selective channels and OFDM systems in frequency flat fading channels. A new criteria is proposed for blind equalization of finite length mobile channels.Peer ReviewedPostprint (published version

    Blind channel equalization using weighted subspace methods

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    This paper addresses the problems of blind channel estimation and symbol detection with second order statistics methods from the received data. It can be shown that this problem is similar to direction of arrival (DOA) estimation, where many solutions like the MUSIC algorithm orPeer ReviewedPostprint (published version

    Diversity techniques for blind channel equalization in mobile communications

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    A blind algorithm for channel distortion compensation is presented which can be employed in spatial or temporal diversity receivers. The proposed technique can be used in frequency selective and frequency flat fading mobile channels, using burst transmission schemes in the first case and OFDM modulation in the second one. The algorithm is base on a deterministic criteria and is suited for estimation when short sets of data are available.Peer ReviewedPostprint (published version

    Fractional biorthogonal partners in channel equalization and signal interpolation

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    The concept of biorthogonal partners has been introduced recently by the authors. The work presented here is an extension of some of these results to the case where the upsampling and downsampling ratios are not integers but rational numbers, hence, the name fractional biorthogonal partners. The conditions for the existence of stable and of finite impulse response (FIR) fractional biorthogonal partners are derived. It is also shown that the FIR solutions (when they exist) are not unique. This property is further explored in one of the applications of fractional biorthogonal partners, namely, the fractionally spaced equalization in digital communications. The goal is to construct zero-forcing equalizers (ZFEs) that also combat the channel noise. The performance of these equalizers is assessed through computer simulations. Another application considered is the all-FIR interpolation technique with the minimum amount of oversampling required in the input signal. We also consider the extension of the least squares approximation problem to the setting of fractional biorthogonal partners
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