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1.
To realize joint optimization of spatial diversity and equalization combining in the intersymbol interference (ISI) channel, an iterative equalization combining algorithm is proposed. The proposed algorithm uses the coefficients of Turbo equalization to calculate the combination weights without estimating the signal to noise ratio in each diversity branch. The equalized symbols from different diversity branches are combined, and the extrinsic information output from the decoder is fed back to the equalizers, so as to exchange soft information between the equalizers and the decoder. The performance of the proposed algorithm is analyzed using the extrinsic information transfer (EXIT) chart and verified by simulations. Results show that our approach fully exploits time domain information from the multipath channel and spatial domain information from multi receiving antennas, which efficiently improve the performance of the receiver in the severe ISI channel. 相似文献
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Recently, considerable amount of attention is being given to the field of wavelets and wavelet packets. It has found numerous
applications in signal representation, image compression and applied mathematics.
In this paper, we present a channel equalization method based on wavelet packets. The proposed equalizer structure is based
on the fact that for sufficiently narrowband sequences, a non-ideal channel can be modelled as an attenuation and delay. If
the data sequence is used to modulate a set of narrowband wavelet packets, then no equalization is required at the receiver
end. The equalization problem reduces to that of determining the delay introduced by the channel for each of the wavelet packets.
A minimum square variance algorithm for adaptively choosing the delay has been proposed. This algorithm has been shown to
perform as desired analytically in a simple delay channel case. Simulations have been used to study its performance in the
non-ideal channel’s case and the results corroborate theoretical predictions. 相似文献
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José Martínez-Aroza Ramón Román-Roldán 《Multidimensional Systems and Signal Processing》1995,6(1):7-35
A multiresolution analysis of digital gray-level images is presented. A gray-level multi-scale framework is determined from two main assumptions: the gray scale is binary at the finest spatial resolution, and the gray levels of composed regions are obtained additively. In order to interrelate the gray-level histograms of the same image at different resolutions, probabilistic linear models are developed, which are then applied for estimation. Linear-optimization theory is used as a way of constructing such models. A general procedure for image processing is sketched, based on gray-level estimation. A versatile algorithm for nonlinear filtering is derived. Some examples of prospective applications are given.This work was partially supported by grant TIC91-646 from the DGYCIT of the Spanish Government. 相似文献
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本文介绍了根据信号码的相互独立性,利用噪声情况下盲信号分离的原理,实现非最小相位通道特性的盲均衡。 相似文献
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MIMO系统的自适应均衡技术研究 总被引:1,自引:1,他引:0
研究了用于MIMO系统的自适应均衡的几种算法,比较了最小均方算法(LMS)、递归最小二乘算法(RLS)、判决反馈算法(DFE)、格型梯度自适应均衡算法(GALE)和格型最小二乘自适应均衡算法(LSALE)。文章的最后给出了仿真结果及结论。 相似文献
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