multimodulus algorithms (MMA) based adaptive blind equalizers mitigate inter-symbol interference in a digital communication system by minimizing dispersion in the quadrature components of the equalized sequence in a d...
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multimodulus algorithms (MMA) based adaptive blind equalizers mitigate inter-symbol interference in a digital communication system by minimizing dispersion in the quadrature components of the equalized sequence in a decoupled manner, i.e., the in-phase and quadrature components of the equalized sequence are used to minimize dispersion in the respective components of the received signal. These unsupervised equalizers are mostly incorporated in bandwidth-efficient digital receivers (wired, wireless or optical) which rely on quadrature amplitude modulation based signaling. These equalizers are equipped with nonlinear error-functions in their update expressions which makes it a challenging task to evaluate analytically their steady-state performance. However, exploiting variance relation theorem, researchers have recently been able to report approximate expressions for steady-state excess mean square error (EMSE) of such equalizers for noiseless but interfering environment. In this work, in contrast to existing results, we present exact steady-state tracking analysis of two multimodulus equalizers in a non-stationary environment. Specifically, we evaluate expressions for steady-state EMSE of two equalizers, namely the MMA2-2 and the beta MMA. The accuracy of the derived analytical results is validated using different set experiments and found in close agreement. (C) 2014 Elsevier B.V. All rights reserved.
For improving the equalization performance of higher-order QAM signals, a generalized multi-modulus blind equalization algorithm based on chaos artificial fish swarm optimization is proposed. In this proposed algorith...
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For improving the equalization performance of higher-order QAM signals, a generalized multi-modulus blind equalization algorithm based on chaos artificial fish swarm optimization is proposed. In this proposed algorithm, according to the prior information of higher-order QAM signal constellations, chaotic artificial fish swarm algorithm is fused to generalized multi-modulus blind equalization algorithm. Accordingly, the proposed algorithm uses rapid global optimum searching ability of chaotic artificial fish swarm algorithm(CAFSA) to initialize equalizer weight vector and adjusts adaptively modulus value of objective function in the equalizer vector iterations. The theoretical analyses and computer simulations indicate that the proposed algorithm outperforms generalized multimodulus algorithm(GMMA) and artificial fish swarm algorithm based GMMA(AFSA-GMMA) in mean square error and convergence rate, which is more efficient for high-order QAM signals.
This paper proposes a space-time semi-blind equalizer (ST-SBE) for dispersive multiple-input multiple-output (MIMO) communication systems that employ high throughput quadrature amplitude modulation (QAM) signals. A no...
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This paper proposes a space-time semi-blind equalizer (ST-SBE) for dispersive multiple-input multiple-output (MIMO) communication systems that employ high throughput quadrature amplitude modulation (QAM) signals. A novel cost function (CF) that integrates multimodulus algorithm (MMA) with soft decision-directed (SDD) scheme is established to efficiently obtain the weight vector associated with the ST-SBE. In the ST-SBE, a very short training sequence is used to provide a rough initial least squares estimate of the weight vector. An efficient modified Newton method (MNM) for minimizing the established cost function is proposed to fast search the optimal weight vector. Very interestingly, we prove that the proposed MNM has the same quadratic order of convergence as Newton methods. In addition, the proposed MNM has much lower computational complexity than Newton methods. Simulation results are provided to demonstrate that the ST-SBE has better performances than the gradient-Newton (GN)-based concurrent constant modulus algorithm (CMA) with SDD scheme (GN-CMA+SDD).
Polarization-division multiplexing (PDM) has emerged as a promising technique for increasing data rates without increasing symbol rates. However, the distortion effects of the fiber transmission medium poses severe ba...
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ISBN:
(纸本)9781479975051
Polarization-division multiplexing (PDM) has emerged as a promising technique for increasing data rates without increasing symbol rates. However, the distortion effects of the fiber transmission medium poses severe barriers for the implementation of this technological alternative. Especially, due to the fiber-induced polarization fluctuation orthogonally transmitted PDM signals are mixed at the receiver input. Therefore, a receiver compensation structure needs to be implemented to recover the original orthogonal transmitted components from their mixtures at the end of the fiber channel. This is in fact the focus of this article where a receiver algorithm is based on a recently proposed minimum entropy equalization scheme exploiting the maximization of (an enhanced) energy cost function subject to the magnitude boundedness of (incoming) digital communication signals. Through the use of this scheme, new receiver algorithms for recovering the original polarization signals in an adaptive manner are proposed. The key feature of these algorithms is that they can achieve high equalization performance while maintaining the algorithmic complexity in a fairly low level that is suitable for implementation in optical fiber communication receivers. The performance of these algorithms for a square-QAM based coherent polarization division multiplexed system are illustrated through some simulation examples.
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