A unified framework for SNR mismatch in turbo algorithms

Ke Xu, B. Shahrrava, Jianwei Wan
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引用次数: 1

Abstract

In this paper, we propose a unified framework to examine the effect of SNR mismatch on the performance of turbo algorithms, such as turbo equalization and turbo decoding. The proposed framework is based on a general model for a biased estimate of the signal-to-noise ratio (SNR) of the channel. It is shown how the estimation model can unify previously SNR mismatch models, which become special cases. Finally, simulation results show the effect of SNR mismatch on the bit error rate (BER) performance of a turbo equalizer based on the biased estimate of the channel SNR
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turbo算法中信噪比失配的统一框架
在本文中,我们提出了一个统一的框架来研究信噪比不匹配对turbo算法性能的影响,如turbo均衡和turbo解码。所提出的框架是基于信道信噪比(SNR)的有偏估计的一般模型。说明了估计模型如何统一以往的特殊情况下的信噪比失配模型。最后,仿真结果显示了信噪比不匹配对基于信道信噪比偏差估计的turbo均衡器误码率性能的影响
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