Analysis of the Multimodulus Blind Equalization Algorithm in QAM Communication Systems

Yuan, Jenq-Tay; Tsai, Kun-Da

doi:10.1109/tcomm.2005.855017

Cited by 89 publications

(38 citation statements)

References 7 publications

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“…, which is exactly the result shown in [9] for the square QAM during the transient operation. This section is mainly concerned with the magnitude of h(k) with maximum modulus [i.e., r(k)=max(|h(k)|)]and…”

Section: Dynamic Phase Tracking Using −∇ θ J Mmasupporting

confidence: 88%

“…The analysis in [9], which concerns only the square constellations, indicates that the MMA can remove inter-symbol interference (ISI) and simultaneously correct the phase error. However, when the transmitted symbols are drawn from a QAM constellation having an odd number of bits per symbol (N = 2 2i+1 , i = 2,3,...), the N-points constellations can be arranged into an oblong constellation [14], [15] Fig.…”

Section: Multimodulus Blind Equalization Algorithmmentioning

confidence: 99%

“…Consequently, (9) and (10) given k = M suffice to determine r 2 + (M) and r 2 − (M): The following form for the four stationary points along θ(k)=0, π/2, π,3π/2 for each of the M non-zero components of h n (for oblong constellations only) can thus be derived…”

Section: Stationary Points Of Mma Using Oblong Constellationsmentioning

confidence: 99%

“…It has been shown in [9] that the following form for all possible stationary points of the MMA (for square and cross constellations), except for r(k)=0, can be expressed as…”

Section: Two Special Cases: Square and Cross Constellationsmentioning

confidence: 99%

See 3 more Smart Citations

Multimodulus Blind Equalization Algorithm Using Oblong QAM Constellations for Fast Carrier Phase Recovery

Yuan¹,

Lin²

2011

Vehicular Technologies: Increasing Connectivity

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Section: Dynamic Phase Tracking Using −∇ θ J Mmasupporting

confidence: 88%

Section: Multimodulus Blind Equalization Algorithmmentioning

confidence: 99%

Section: Stationary Points Of Mma Using Oblong Constellationsmentioning

confidence: 99%

“…It has been shown in [9] that the following form for all possible stationary points of the MMA (for square and cross constellations), except for r(k)=0, can be expressed as…”

Section: Two Special Cases: Square and Cross Constellationsmentioning

confidence: 99%

See 2 more Smart Citations

Multimodulus Blind Equalization Algorithm Using Oblong QAM Constellations for Fast Carrier Phase Recovery

Yuan¹,

Lin²

2011

Vehicular Technologies: Increasing Connectivity

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“…and ε 0 , ε 2 , ε 4 and λ 2 , λ 4 are given in (13) and (43), respectively. β ANEW and µ ANEW are positive step size parameters.…”

Section: Simulationmentioning

confidence: 99%

New Lagrange Multipliers for the Blind Adaptive Deconvolution Problem Applicable for the Noisy Case

Pinchas

2016

Entropy

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Abstract:Recently, a new blind adaptive deconvolution algorithm was proposed based on a new closed-form approximated expression for the conditional expectation (the expectation of the source input given the equalized or deconvolutional output) where the output and input probability density function (pdf) of the deconvolutional process were approximated with the maximum entropy density approximation technique. The Lagrange multipliers for the output pdf were set to those used for the input pdf. Although this new blind adaptive deconvolution method has been shown to have improved equalization performance compared to the maximum entropy blind adaptive deconvolution algorithm recently proposed by the same author, it is not applicable for the very noisy case. In this paper, we derive new Lagrange multipliers for the output and input pdfs, where the Lagrange multipliers related to the output pdf are a function of the channel noise power. Simulation results indicate that the newly obtained blind adaptive deconvolution algorithm using these new Lagrange multipliers is robust to signal-to-noise ratios (SNR), unlike the previously proposed method, and is applicable for the whole range of SNR down to 7 dB. In addition, we also obtain new closed-form approximated expressions for the conditional expectation and mean square error (MSE).

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Orbital Angular Momentum‐based Wireless Communications: Designs and Implementations

Willner

Yan

Ren

et al. 2016

Signal Processing for 5G

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Analysis of the Multimodulus Blind Equalization Algorithm in QAM Communication Systems

Cited by 89 publications

References 7 publications

Multimodulus Blind Equalization Algorithm Using Oblong QAM Constellations for Fast Carrier Phase Recovery

Multimodulus Blind Equalization Algorithm Using Oblong QAM Constellations for Fast Carrier Phase Recovery

New Lagrange Multipliers for the Blind Adaptive Deconvolution Problem Applicable for the Noisy Case

Orbital Angular Momentum‐based Wireless Communications: Designs and Implementations

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