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Description: Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique.
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Size: 134537 |
Author: zhang |
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Description: Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique. -Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique.
Platform: |
Size: 134144 |
Author: zhang |
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Description: This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
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Size: 102400 |
Author: Lee |
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Description: Matlab程序，用于比较线性均衡器、判决反馈均衡器(DFE)、盲最大似然序列估计均衡器(MLSE)等误码率性能。-Matlab procedures used to compare the linear equalizer, decision feedback equalizer (DFE), Blind maximum likelihood sequence estimation equalizer (MLSE), such as bit error rate performance.
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Size: 148480 |
Author: yyc |
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Description: 信道均衡
目的和原理
MLSE、 DFE、 ZF/LMMSE均衡
干扰抵消
原理
导频干扰抵消和多码道干扰抵消
HSDPA简介
主要信道
接收机结构
-Channel equalization purposes and principles of MLSE, DFE, ZF/LMMSE equalizer pilot interference cancellation principle of interference cancellation and multi-code channel interference cancellation receiver HSDPA channel structure of the main profile
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Size: 1362944 |
Author: 王琴 |
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Description: MATLAB 仿真MLSE，DFE，FFE均衡效率比较。-MATLAB simulation of MLSE, DFE, FFE balance efficiency comparisons.
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Size: 161792 |
Author: 魏明川 |
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Description: 均衡效果好，这是基于最大似然估计的均衡器-With the development of high-speed optical fiber communication systems, polarization
mode dispersion (PMD) has become a vital limiting factor. However, the traditional
compensation methods which in optical domain have the disadvantages of complexity and cost.
In recent years, the compensation methods which in electronic domain are given more attention
because of their outstanding price advantage and their strong adaptability.
The maximum-likehihood sequence estimation (MLSE) equalizer based on the Viterbi
algorithm was designed in this paper.The MLSE equalizer can effectively compensate the
intersymbol interference caused by polarization mode dispersion (PMD). First, the background
and the spectrum of the text were introduced also the principles of PMD and the FFE/DFE
equalizer were analysed. Second, the principles of Viterbi and the structure of MLSE were
researched also the MLSE equalizer was simulated with the Matlab program in the optical fiber
communication systems. T
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Size: 1383424 |
Author: 心语蜗牛 |
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Description: 均衡技术课件，对横向滤波器，最大似然序列检测和判决反馈均衡器均进行了详细介绍-PPT for equizer, describe the MLSE, transversal filter and DFE
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Size: 99328 |
Author: 张凯 |
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Description: 展示了线性、DFE、MLSE均衡器的信噪比性能，并通过蒙特卡罗模拟信道估计结果确定。-This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
Platform: |
Size: 112640 |
Author: |
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