An algorithm Of constantmodulus Signal Separation based on Minimal Rayleigh Entropy (MRE-AOCMSS) is presented. Utilizing an error cost function, a novel covariance matrix is constructed. Then an optimal weight vector...
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An algorithm Of constantmodulus Signal Separation based on Minimal Rayleigh Entropy (MRE-AOCMSS) is presented. Utilizing an error cost function, a novel covariance matrix is constructed. Then an optimal weight vector used to extract the desired constantmodulus signal is obtained via minimizing the Rayleigh entropy. Employing the algorithm, interferences can be cancelled effectively. The algorithm is still valid when co-channel interference signal's power is much greater than the desired signal's power. The simulation results indicate that this MRE-AOCMSS algorithm is effective in terms of constantmodulus signal separation and interference suppression.
The constant modulus algorithm (CMA) is an excellent technique for blind channel equalization. Recently signed error version of CMA (SE-CMA) and dithered signed error version (DSE-CMA,) have been proposed which afford...
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The constant modulus algorithm (CMA) is an excellent technique for blind channel equalization. Recently signed error version of CMA (SE-CMA) and dithered signed error version (DSE-CMA,) have been proposed which afford overall computational efficiency. We propose three different error functions for faster convergence. This would be essential for communication systems, which cannot afford a high startup delay or for systems, where the channel's impulse response is rapidly fluctuating. One of these algorithms relies on the idea of a variable step size, which increases the rate of convergence.
The constant modulus algorithm (CMA) is commonly used for first stage blind equalization applications. CMA's main advantage is that it will open the eye based on the received signal only. Decision directed (DD) eq...
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ISBN:
(纸本)0780374029
The constant modulus algorithm (CMA) is commonly used for first stage blind equalization applications. CMA's main advantage is that it will open the eye based on the received signal only. Decision directed (DD) equalization is often used as it provides a lower mean square error (MSE) in the equalized signal. Obvious from its name, DD equalization requires estimates of the transmitted symbols in order to adapt the equalizer - the eye must be open. This paper considers an elegant method to transition between CMA and DD equalization (in a decision feedback equalizer structure). A conventional "brute force" approach to perform the transition is to determine the filter coefficients for the DD equalizer through a MMSE design criterion based on the inverse CMA filter coefficients. This may cause a large procession delay at the point of transition between filter types and requires significant computations. The algorithm in this paper is low complexity and does not require a large processing delay when transitioning from CMA to DD LMS.
This paper proposes a new multitarget constantmodulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant mod...
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This paper proposes a new multitarget constantmodulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant modulus algorithm (D-WD-CMA). In the new algorithm, the pre-despreading is applied to multitarget arrays to remove some multiple access inter- ferences. After that the received signal is subjected to wavelet de-noising to reduce some noise, and used in CMA adaptive iteration for signal separation. Simulation results showed that the proposed algorithm performed better than the traditional CMA algorithm.
In a multi-user direct sequence code division multiple access (DS-CDMA) system, retrieval of the transmitted signals with a conventional receiver is difficult when there is chip asynchronism, multipath propagation and...
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ISBN:
(纸本)0780374029
In a multi-user direct sequence code division multiple access (DS-CDMA) system, retrieval of the transmitted signals with a conventional receiver is difficult when there is chip asynchronism, multipath propagation and the associated near-far problem. The results show that despite these problems an adaptive linear receiver based on a mixed cross correlation and constant modulus algorithm (CC-CMA) has the potential to retrieve all users simultaneously. In this paper, we propose several algorithms based on Quasi-Newton type algorithms. Compared with the conventional CC-CMA algorithm, the proposed algorithms achieve faster convergence at low computational cost. Simulations support the improved convergence properties of the algorithm.
The constant modulus algorithm (CMA)enjoys widespread popularity as methods for blind beamforming and equalization of communication signals. CMA is straightforward to implement, robust, and computationally of modest c...
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ISBN:
(纸本)0780374886
The constant modulus algorithm (CMA)enjoys widespread popularity as methods for blind beamforming and equalization of communication signals. CMA is straightforward to implement, robust, and computationally of modest complexity. Despite its effectiveness and apparent simplicity, adaptive implementation of the CMA comes along with several complicating factors that have never really been solved. In particular, convergence can be unpredictable and slow depending on the stepsize. In this paper, Convergence behaviors of the constant modulus algorithm based on "1-2" cost, function (CMA(1-2)) and "2-1" cost function (CMA(2-1)) are investigated. We found that certain signal could be quickly removed from the output data choosing special stepsize if at least two signals were with different power. Simulation examples confirm the results.
This paper presents an adaptive autoregressive (AR) approach to the blind image deconvolution problem which has several advantages over standard adaptive FIR filters. There is no need to figure out the optimum filter ...
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This paper presents an adaptive autoregressive (AR) approach to the blind image deconvolution problem which has several advantages over standard adaptive FIR filters. There is no need to figure out the optimum filter support when using an AR deconvolution filter because it is the same as the support of the blur. Thus there is no distortion introduced by the finite support of the FIR filter. While an FIR filter provides an approximate inverse to the blur at convergence, the AR filter converges to an approximation of the blur itself. Hence, the method can be used for blur identification. Simulations suggest that convergence of the adaptive AR filter coefficients occur rapidly and the improvement in signal-to-noise ratios are higher than in the FIR case for a given blur (and with the same step-size for the adaptive algorithms). When the adaptive AR method is derived naively to minimize the dispersion, it requires a recursion within a recursion which is computationally complex. We propose a simplification that removes the inner recursion, and prove conditions under which this simplification is valid when dealing with binary images. Simulations are used to show that the method may also be applied to certain multi-valued images as well. Copyright (c) 2005 John Wiley & Sons, Ltd.
The blind equalizers based on complex valued feedforward neural networks, for linear and nonlinear communication channels, yield better performance as compared to linear equalizers. The learning algorithms are, genera...
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The blind equalizers based on complex valued feedforward neural networks, for linear and nonlinear communication channels, yield better performance as compared to linear equalizers. The learning algorithms are, generally, based on stochastic gradient descent, as they are simple to implement. However, these algorithms show a slow convergence rate. In the blind equalization problem, the unavailability of the desired output signal and the presence of nonlinear activation functions make the application of recursive least squares algorithm difficult. In this letter, a new scheme using recursive least squares algorithm is proposed for blind equalization. The learning of weights of the output layer is obtained by using a modified version of constant modulus algorithm cost function. For the learning of weights of hidden layer neuron space adaptation approach is used. The proposed scheme results in faster convergence of the equalizer.
Gaussian frequency shift keying is the modulation scheme specified for Bluetooth. Signal adversities typical in Bluetooth networks include AWGN, multipath propagation, carrier frequency, and modulation index offsets. ...
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Gaussian frequency shift keying is the modulation scheme specified for Bluetooth. Signal adversities typical in Bluetooth networks include AWGN, multipath propagation, carrier frequency, and modulation index offsets. In our effort to realise a robust but efficient Bluetooth receiver, we adopt a high-performance matched-filter-based detector, which is near optimal in AWGN, but requires a prohibitively costly filter bank for processing of K bits worth of the received signal. However, through filtering over a single bit period and performing phase propagation of intermediate results over successive single-bit stages, we eliminate redundancy involved in providing the matched filter outputs and reduce its complexity by up to 90% (for K = 9). The constantmodulus signal characteristic and the potential for carrier frequency offsets make the constant modulus algorithm (CMA) suitable for channel equalisation, and we demonstrate its effectiveness in this paper. We also introduce a stochastic gradient-based algorithm for carrier frequency offset correction, and show that the relative rotation between Successive intermediate filter outputs enables us to detect and correct offsets in modulation index.
An operational system for image transmission through the ionospheric channel is presented. For a range of 780 kin, the 'high' data transfer rate attains 30 kbits/s in a 9 kHz bandwidth with the implementation ...
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An operational system for image transmission through the ionospheric channel is presented. For a range of 780 kin, the 'high' data transfer rate attains 30 kbits/s in a 9 kHz bandwidth with the implementation of a blind spatio-temporal equalisation based on the constant modulus algorithm. This value significantly exceeds the current standard for HF modems (4.8 kbits/s). The quality of the transmitted images appears to be good compared with the original.
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