The constant modulus algorithm(CMA) is recognized as the most widely used algorithm in blind channel equalization practice. However, the CMA cost function exhibits local minima, which often leads to ill-convergence. T...
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The constant modulus algorithm(CMA) is recognized as the most widely used algorithm in blind channel equalization practice. However, the CMA cost function exhibits local minima, which often leads to ill-convergence. This paper proposes a concurrent equalizer, in which a Soft Decision Directed(SDD) equalizer operates cooperatively with a CMA equalizer, controlled through a non-linear link that depends on the system a priory state. The simulation results show that the proposed equalizer has faster convergence rate and lower steady-state mean square error than the CMA equalizer.
In the digital transmission system, constant modulus algorithm(CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constantmodulus sign...
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In the digital transmission system, constant modulus algorithm(CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constantmodulus signals such as higher-order PAM signals, the CMA just achieve moderate steady-state mean square error(MSE) which may not be sufficient for the system to obtain adequate performance. By studying the amplitude relationship between different constellations of PAM signals, a new amplitude transformation method is proposed. According to such method the non-constantmodulus signals can be changed to be constantmodulus, and then using it to the CMA the zero steadystate MSE can be obtained. The efficiency of the proposed method is proved by computer simulations.
In the digital transmission system, constant modulus algorithm(CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constantmodulus sign...
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In the digital transmission system, constant modulus algorithm(CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constantmodulus signals such as higher-order QAM signals, the CMA just achieve moderate steady-state mean square error(MSE) which may not be sufficient for the system to obtain adequate performance. By studying the amplitude relationship between different constellations of QAM signals, a new amplitude transformation method is proposed. According to such method the non-constantmodulus signals can be changed to be constantmodulus, and then using it to the CMA the zero steadystate MSE can be obtained. The efficiency of the proposed method is proved by computer simulations.
This contribution considers semi-blind adaptive equalization for communication systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal ...
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This contribution considers semi-blind adaptive equalization for communication systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the equalizer, are first utilized to provide a rough initial least-squares estimate of the equalizer's weight vector. A novel gradient-Newton concurrent constant modulus algorithm and soft decision-directed scheme are then applied to adapt the equalizer. The proposed semi-blind adaptive algorithm is capable of converging fast and accurately to the optimal minimum mean-square error equalization solution. Simulation results obtained demonstrate that the convergence speed of this semi-blind adaptive algorithm is close to that of the training-based recursive least-square algorithm. Copyright (C) 2009 John Wiley & Sons, Ltd.
In digital communication systems, the constant modulus algorithm (CMA) for blind multiuser detector has some disadvantage such as slow convergence speed and weight phase rotation. In this paper, we put forward a novel...
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In digital communication systems, the constant modulus algorithm (CMA) for blind multiuser detector has some disadvantage such as slow convergence speed and weight phase rotation. In this paper, we put forward a novel receiver, which combines CMA blind adaptive multiuser detection and particle swarm optimization (PSO) technique in frequency domain for multi-carrier direct sequence code division multiple access (MC DS-CDMA) systems. By this approach we present an adaptive multistage structure based on PSO technique. In this structure, the weights are obtained by PSO technique between the received signal and its estimate through a CMA. The resulting weights contain reliability information for the hard decisions made in the previous stage. The simulation results show that BER performance of the PSO-based CMA blind multiuser detector is superior to that of steepest decreasing constant modulus algorithm (SDCMA), linearly constrained constant modulus algorithm (LCCMA), CMA based multiuser detection and is worthy due to its significant detection performance to achieve desirable improvement in convergence speed and tractability.
This paper analyzes the convergence of the constant modulus algorithm (CMA) in a decision feedback equalizer using only a feedback filter. Several works had already observed that the CMA presented a better performance...
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This paper analyzes the convergence of the constant modulus algorithm (CMA) in a decision feedback equalizer using only a feedback filter. Several works had already observed that the CMA presented a better performance than decision directed algorithm in the adaptation of the decision feedback equalizer, but theoretical analysis always showed to be difficult specially due to the analytical difficulties presented by the constantmodulus criterion. In this paper, we surmount such obstacle by using a recent result concerning the CM analysis, first obtained in a linear finite impulse response context with the objective of comparing its solutions to the ones obtained through the Wiener criterion. The theoretical analysis presented here confirms the robustness of the CMA when applied to the adaptation of the decision feedback equalizer and also defines a class of channels for which the algorithm will suffer from ill-convergence when initialized at the origin.
Spectrally-efficient optical communications systems employ polarization division multiplexing (PDM) as a practical solution, in order to double the capacity of a fiber link. Polarization demultiplexing can be performe...
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Spectrally-efficient optical communications systems employ polarization division multiplexing (PDM) as a practical solution, in order to double the capacity of a fiber link. Polarization demultiplexing can be performed electronically, using polarization-diversity coherent optical receivers. The primary goal of this paper is the optimal design, using the maximum-likelihood criterion, of polarization-diversity coherent optical receivers for polarization-multiplexed optical signals, in the absence of polarization mode dispersion (PMD). It is shown that simultaneous joint estimation of the symbols, over the two received states of polarization, yields optimal performance, in the absence of phase noise and intermediate frequency offset. In contrast, the commonly used zero-forcing polarization demultiplexer, followed by individual demodulation of the polarization-multiplexed tributaries, exhibits inferior performance, and becomes optimal only if the channel transfer matrix is unitary, e. g., in the absence of polarization dependent loss (PDL), and if the noise components at the polarization diversity branches have equal variances. In this special case, the zero-forcing polarization demultiplexer can be implemented by a 2 2 lattice adaptive filter, which is controlled by only two independent real parameters. These parameters can be computed recursively using the constant modulus algorithm (CMA). We evaluate, by simulation, the performance of the aforementioned zero-forcing polarization demultiplexer in coherent optical communication systems using PDM quadrature phase shift keying (QPSK) signals. We show that it is, by far, superior, in terms of convergence accuracy and speed, compared to conventional CMA-based polarization demultiplexers. Finally, we experimentally test the robustness of the proposed constrained CMA polarization demultiplexer to realistic imperfections of polarization-diversity coherent optical receivers. The PMD and PDL tolerance of the proposed demultiple
We employ minimum entropy deconvolution principle for blind equalization of complex digital signals. In essence, we maximize the output energy, constrain the equalizer output not to exceed certain level and obtain an ...
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We employ minimum entropy deconvolution principle for blind equalization of complex digital signals. In essence, we maximize the output energy, constrain the equalizer output not to exceed certain level and obtain an adaptive solution capable of opening a closed-eye with the recovery of true energy of signal. We provide evidence of good performance in comparison to existing adaptive methods, like CMA and its variants, through simulations.
A semi-blind adaptive beamforming scheme is proposed for wireless systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver a...
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A semi-blind adaptive beamforming scheme is proposed for wireless systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna arrayts elements, are first utilised to provide a rough initial least squares estimate of the beamformer＇s weight vector. A concurrent constant modulus algorithm and soft decision-directed scheme is then applied to adapt the beamformer. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study.
In this paper, we analyze the applicability of constant modulus algorithm (CMA), one of the most widely used and tested blind equalization technique to blind image deconvolution. With a detailed mathematical analysis,...
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ISBN:
(纸本)9781424479078
In this paper, we analyze the applicability of constant modulus algorithm (CMA), one of the most widely used and tested blind equalization technique to blind image deconvolution. With a detailed mathematical analysis, we show that the strong correlation between the neighboring spatial locations found in natural images becomes a major constraint on the convergence of CMA. In order to overcome this constraint, we introduce a novel image pixel correlation model in relation with natural image statistics. Based on this model, a segmented blind image deconvolution through CMA is proposed. The robustness of the proposed algorithm with natural images is discussed in terms of efficiency and effectiveness.
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