• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.115-120
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• 2011

This paper is concerned with the performance comparison of CR-CMA (Coordinate Reduction-CMA) and CM-CMA (Constellation Matching-Constant Modulus Algorithm) that is used for improving the convergence characteristic and residual intersymbol interference which are used as the performance index for an adaptive equalizer. The equalizer is used to reduce the distortion caused by the intersymbol interference on the wireless and the wired band-limited channel, and the blind method which does not need for extra bandwidth by the training sequence of digital code are researched. Recently, by using the merit of simple operation in the CMA, the performance improvement is obtained by the modifying the cost function of it. In this paper, the new algorithm, CR-CMA and CM-CMA, the performance analysis are performed and compared by computer simulation. The CR-CMA has a superior equalization characteristics in the recovered constellation, convergence speed and residual intersymbol interference than the CM-CMA by computer simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.107-114
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• 2012

In this paper, the concerned existing blind equalizer convergence rate and residual inter-symbol interference using constellation reduced and cost function by separation the real part and an imaginary part, the dual structure CR-CMA(constellation Reduction CMA). The CMA methed compensates amplitude but does no compensate phase, On the other hand, The CMA method compensates both the amplitude and the phase but it has the convergence rate problem, and the MCMA method is a way to solve the phase problem of CMA method compensates both the amplitude and the phase after respectively calculating the real part and imaginary part components. Proposal a new method that the dual structure of CR-CMA, the cost function and error function and respectively calculating the real part and imaginary part components can advantages by improving the CMA and the MCMA algorithms so that the amplitude and phase retrieval and constellation reduce the residual ISI and faster convergence rate and performance is good SER (Symbol Error Ratio) was confirmed by computer simulations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.107-113
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• 2011

This paper is concerned with the CR-CMA (Coordinate Reduction-Constant Modulus Algorithm) adaptive equalization algorithm using the coordinate reduction in order to improve the convergence characteristic and residual intersymbol interference which are used as the performance index for an adaptive equalizer. The equalizer is used to reduce the distortion caused by the intersymbol interference on the wireless and the wired band-limited channel that connect the transmitting system and receiving system. The CMA is widely known as the representative algorithm for equalization. In order to transmitting the mass information with a high speed through the channels, a fast convergence speed in the equalizer performance that is able to minimize overhead needed for equalization is acquired. In this paper, we introduce the new cost function to reduce the constellation of received signal at the input stage of a equalizer. It reduce the error at the steady equalization state. By the computer simulation, we confirmed that the proposed CR-CMA algorithm has the faster convergence speed and the smaller residual intersymbole interference than the conventional CMA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.384-391
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• 2003

Blind channel identification and equalization attempt to identify the communication channel and to remove the inter-symbol interference caused by a communication channel without using any known trainning sequences. In this paper, we propose a blind adaptive channel identification and equalization algorithm with phase offset compensation for single-input multiple-output (SIMO) channel. It is based on the one-step forward multichannel linear prediction error method and can be implemented by an RLS algorithm. Phase offset problem, we use a blind adaptive algorithm called the constant modulus derotator (CMD) algorithm based on condtant modulus algorithm (CMA). Moreover, unlike many known subspace (SS) methods or cross relation (CR) methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch.