This paper quantifies the adaptive performance of a blind adaptive multiuser detector (MUD) based on the linearly constrained constant modulus algorithm (LCCMA) in both a stationary and nonstationary channel. A framew...
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This paper quantifies the adaptive performance of a blind adaptive multiuser detector (MUD) based on the linearly constrained constant modulus algorithm (LCCMA) in both a stationary and nonstationary channel. A framework is developed to apply the feedback analysis method to analyzing adaptive MUD schemes. A closed-form expression for the excess mean square error (EMSE) of LCCMA blind adaptive MUD in a CDMA communications system is derived for both of the steady-state and tracking cases. The effects of additive noise and multiple access interference are considered. A transient analysis is performed that predicts the learning curve of the adaptive filter. Computer simulation is used to verify the accuracy of the analysis.
A new concurrent scheme for blind equalization suitable for 16-QAM signal is proposed. It combines Modified modulusalgorithm (MCMA) and Modified Decision Directed (MDD) algorithm. By exploiting the inherent structura...
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ISBN:
(纸本)9781424448562
A new concurrent scheme for blind equalization suitable for 16-QAM signal is proposed. It combines Modified modulusalgorithm (MCMA) and Modified Decision Directed (MDD) algorithm. By exploiting the inherent structural relationship between the 4-QAM signal's coordinates and 16-QAM signals' coordinates, another style of cost function for constant modulus algorithm (CMA) is defined, and we have proved that MCMA with such cost function outperforms the conventional CMA considerably. Unfortunately, MCMA has the same inherent defect as CMA which is that it is not sensitivity for phase offset of received signals. So when it occurs, the performance of MCMA will be impaired and even MCMA cannot work. Accordingly for overcoming the shortcomings of MCMA we introduce the Decision Directed (DD) algorithm, and modify it with the same method as MCMA. Consequently the new concurrent blind equalization with MCMA and MUD is proposed. Simulation results with underwater acoustic channel model show that the proposed algorithm achieves satisfactory performance.
Blind equalization based on wavelet neural network optimizing by genetic algorithm was proposed for the conventional gradient algorithm is sensitive to the values of the initial parameters. At beginning, a segment fin...
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ISBN:
(纸本)9781424436927
Blind equalization based on wavelet neural network optimizing by genetic algorithm was proposed for the conventional gradient algorithm is sensitive to the values of the initial parameters. At beginning, a segment finite data was collected for genetic algorithm to get a group of asymptotically optimal initial parameters. And then, gradient-descent algorithm was adopted to train network to trace and compensate the channel characteristic to implement equalization. Convergence and stability analysis of the proposed algorithm is also provided. The goodness of the proposed blind equalization algorithm is demonstrated with the aid of a simulated the non-linear channel.
A new Decision-Feedback Equalizer (DFE) is proposed to overcome Inter-Symbol Interference (ISI) faster in the communication system without the aid of training sequences. Unlike the conventional DFE, the feedforward fi...
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ISBN:
(纸本)9780769537290
A new Decision-Feedback Equalizer (DFE) is proposed to overcome Inter-Symbol Interference (ISI) faster in the communication system without the aid of training sequences. Unlike the conventional DFE, the feedforward filter component and the feedback filter component in the proposed DFE operate with constant modulus algorithm (CMA) and Decision-Directed (DD) algorithm respectively. It makes full use of the advantages of the CMA's "eye-opened" ability and DD's faster convergence rate ability. Consequently the proposed DFE has the faster convergence rate than the conventional DFE which can improve the performance for the system. Simulations with underwater acoustic channels are presented and the simulation results are shown to prove the efficiency of the proposed DFE.
We extend the affine combination of one fast and one slow least mean-square (LMS) filter to blind equalization, considering the combination of two constant modulus algorithms (CMA). We analyze the proposed combination...
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ISBN:
(纸本)9781424423538
We extend the affine combination of one fast and one slow least mean-square (LMS) filter to blind equalization, considering the combination of two constant modulus algorithms (CMA). We analyze the proposed combination in stationary and nonstationary environments verifying that there are situations where the absence of the restriction on the mixing parameter can be advantageous for the combination Furthermore, we propose a combination of two CMAs with different initializations. Preliminary simulations show that this scheme can avoid local minima and eventually can present a faster convergence rate than that of its components.
The presence of non-Gaussian impulsive noise in wireless system can degrade the performance of existing equalizers and signal detectors. In this paper, the problem of blind source separation and equalization for Multi...
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ISBN:
(纸本)9781424436927
The presence of non-Gaussian impulsive noise in wireless system can degrade the performance of existing equalizers and signal detectors. In this paper, the problem of blind source separation and equalization for Multiple Input/Multiple Output systems in heavy-tailed impulsive noise is studied. A generalized multi-user constantmodulus cost function by employing the fractional lower-order constantmodulus proper", of the equalizer input signals as well as the fractional lower-order cross-correlations between them is proposed. The associated adaptive blind equalization algorithm based on a stochastic gradient descent method is defined as fractional lower-order multi-user constant modulus algorithm (FLOS_MU_CMA). Computer simulations are presented to illustrate the performance of the new algorithm.
An adaptive digital filter algorithm that can optimize the signal-to-noise ratio of an antenna array with multiuser signal inputs is presented in this paper. These synchronous communication signals have the constant e...
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ISBN:
(纸本)078039335X
An adaptive digital filter algorithm that can optimize the signal-to-noise ratio of an antenna array with multiuser signal inputs is presented in this paper. These synchronous communication signals have the constant envelope property and are transmitted through a multiple-input/multiple-output (MIMO) linear channel. This multiuser constant modulus algorithm (MU-CMA) using an antenna array can compensate for both interuser (IUI) and intersymbol interference (ISI). The method is derived by minimizing the cost function of the constantmodulus signals as well as cross-correlations between them. The simulation result at the end of this paper shows the performance of this algorithm.
In this paper, we derive a concurrent constant modulus algorithm (CMA) and decision directed (DD) scheme for blind multiuser equalisation, suitable for downlink DS-CDMA systems. Adaptation is performed by concurrently...
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ISBN:
(纸本)0780394038
In this paper, we derive a concurrent constant modulus algorithm (CMA) and decision directed (DD) scheme for blind multiuser equalisation, suitable for downlink DS-CDMA systems. Adaptation is performed by concurrently minimising two cost functions based on either a CM criterion or a DD scheme for all active users. Computer simulations are used to assess the performance of the algorithm.
A new blind adaptive equalization method for constantmodulus signals based on minimizing the approximate negentropy of the estimation error for a finite-length equalizer is presented. We consider the approximate nege...
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A new blind adaptive equalization method for constantmodulus signals based on minimizing the approximate negentropy of the estimation error for a finite-length equalizer is presented. We consider the approximate negentropy using nonpolynomial expansions of the estimation error as a new performance criterion to improve the performance of a linear equalizer using the conventional constant modulus algorithm (CMA). Negentropy includes higher order statistical information and its minimization provides improved convergence, performance, and accuracy compared to traditional methods, such as the CMA, in terms of the bit error rate (BER). Also, the proposed equalizer shows faster convergence characteristics than the CMA equalizer and is more robust to nonlinear distortion than the CMA equalizer.
The constant modulus algorithm (CMA) and subspace approach are both blind algorithms, which are applied in the communication signal processing widely. We combine the CMA with the subspace approach and propose the CM_S...
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The constant modulus algorithm (CMA) and subspace approach are both blind algorithms, which are applied in the communication signal processing widely. We combine the CMA with the subspace approach and propose the CM_SUB blind equalization algorithm. Simulation results show that the proposed CM_SUB algorithm is superior to the traditional CMA algorithm on convergence rate.
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