A soft decision-directed blind equalization algorithm applied to equalization of mobile communication channels

Karaoguz, J.; Ardalan, S.H.

doi:10.1109/icc.1992.268036

Cited by 37 publications

(28 citation statements)

References 9 publications

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“…The bootstrap MAP blind scheme was originally derived in [9] for the 4-QAM case and extended to M -QAM channels in [7], [8], and it has been shown to outperform the CMA+DD scheme, in terms of convergence rate and steady-state performance [10], [11]. A drawback of this bootstrap MAP scheme is that its adaptive process requires L-stage switchings, where L = log 2 (M )/2, and each stage of adaptation needs a different set of algorithm parameters.…”

Section: Introductionmentioning

confidence: 99%

Concurrent constant modulus algorithm and soft decision directed scheme for fractionally-spaced blind equalization

Chen

Chng

2004

2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577)

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The paper proposes a concurrent constant modulus algorithm (CMA) and soft decision-directed (SDD) scheme for lowcomplexity blind equalization of high-order quadrature amplitude modulation channels. Simulation using a fractionally-spaced equalization setting is used to compare the proposed scheme with the recently introduced state-of-art concurrent CMA and decisiondirected (DD) scheme. The proposed CMA+SDD blind equalizer is shown to have simpler computational complexity per weight update, faster convergence speed, and slightly improved steady-state equalization performance, compared with the CMA+DD blind equalizer.

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Section: Introductionmentioning

confidence: 99%

Concurrent constant modulus algorithm and soft decision directed scheme for fractionally-spaced blind equalization

Chen

Chng

2004

2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577)

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“…Karaoguz and Ardalan [13] first suggested this algorithm for 4-QAM (Q = 2) channels. In order to speed up convergence rate and to keep the complexity to a minimum, a multi-stage implementation was proposed [11,12] for high-oder QAM signalling.…”

Section: Bootstrap Map Equalizermentioning

confidence: 99%

“…The bootstrap MAP equalizer was originally derived in [13] for 4-QAM constellation and extended to M-QAM (M > 4) communication channels in [11,12]. The basic idea is to maximize the a posteriori probability density function (PDF) of the equalizer output subject to the equalizer weights.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of two blind FIR equalizers

Chen

Cook

Anderson

2004

Digital Signal Processing

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The paper investigates blind finite-impulse-response (FIR) equalization schemes for quadrature amplitude modulation signalling. We compare a bootstrap maximum a posteriori probability (MAP) equalizer with a recently introduced concurrent constant modulus algorithm (CMA) and decision directed (DD) equalizer (CMA+DD). Both equalizers are known to outperform the CMA considerably in the situations where carrier recovery is performed and the signal constellation is known. The concurrent CMA+DD equalizer has a complexity that is slightly more than twice of the CMA, and the bootstrap MAP equalizer has computational requirements that are only slightly more complex than the CMA. Simulation results indicate that the bootstrap MAP blind FIR equalizer has a faster convergence rate and better steady-state performance than the concurrent CMA+DD blind FIR equalizer, but tuning of the former is more complicated than the latter.

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“…[5] , Chen에 의해 M레벨 QAM (M-QAM) 신호에 대한 등화로 확장되었다 [6] . 그러 나 Chen이 제안한 M-QAM에 대한 GCA는 M에 따라 계산 복잡성이 매우 증가할 뿐만 아니라 [6] , [7] .…”

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“…[2] . 그러므로   은 가우시안 분포하며, 그 확률 밀도 함수는, 송신 신호를 이진 위상 천이 변조 (binary phase shift keying: BPSK) 신호로 가정하 면 다음으로 주어진다 [5], [6] . [5] .…”

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An Adaptive Blind Equalizer Using Gaussian Two-Cluster Model

2012

The Journal of Korean Institute of Communications and Informati

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In this paper, blind equalization technique using Gaussian two-cluster model is proposed. The proposed approach, by modeling the received M-QAM signals as Gaussian distributed two-cluster, minimizes the computational complexity and enhances the reliability of the signal estimates. In addition, by using a nonlinear estimator with variable parameters to estimate the transmitted signal, and by selectively applying the reduced constellation and the original constellation when estimating the signals, the reliability of the signal estimation was further improved. As a result, the proposed approach has improved the performance while reducing the complexity of the equalizer. Through computer simulations for blind equalization of higher-order signals of 64-QAM, it was confirmed that the proposed method showed better performance than traditional approaches. . 아울 러 블라인드 등화는 눈모형을 열리게 하는 것에 중 점을 두기 때문에 눈모형이 열린 이후의 수렴 성능 은, 예를 들면 excess MSE(mean square error) 레

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A soft decision-directed blind equalization algorithm applied to equalization of mobile communication channels

Cited by 37 publications

References 9 publications

Concurrent constant modulus algorithm and soft decision directed scheme for fractionally-spaced blind equalization

Concurrent constant modulus algorithm and soft decision directed scheme for fractionally-spaced blind equalization

A comparative study of two blind FIR equalizers

An Adaptive Blind Equalizer Using Gaussian Two-Cluster Model

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