Quantization based reliable equalization algorithm for turbo DFE and dual-mode blind equalizers

Abhishek Joshi, N. Cho
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Abstract

In this paper we propose a new adaptive equalization technique for Turbo Decision Feedback Equalizers (TDFE) and dual-mode blind equalizers, that takes the advantage of quantization in the probabilistic scheme. In generating the error signal the proposed technique considers the likelihood between the quantized equalizer output and all the constellation points, thus making the receiver insensitive to the decoding errors. The proposed technique achieves lower BER with less computations than other TDFE algorithms. Also a more reliable soft transition between start-up and Decision Directed (DD) mode in blind equalizers is proposed. This technique has been compared with Benveniste-Goursat, Stop-and-Go and Lim's soft transition algorithm. It is shown that the proposed approach is superior and more robust under different channel and SNR conditions.
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基于量化的涡轮DFE可靠均衡算法及双模盲均衡器
本文针对Turbo决策反馈均衡器(TDFE)和双模盲均衡器提出了一种新的自适应均衡技术,该技术利用了概率方案中量化的优势。在产生误差信号时,该技术考虑了量化均衡器输出与所有星座点之间的似然关系,从而使接收机对解码误差不敏感。与其他TDFE算法相比,该算法的误码率更低,计算量更少。提出了一种更可靠的盲均衡器在启动模式和定向决策模式之间的软转换方法。并与benvenist - goursat、Stop-and-Go和Lim的软过渡算法进行了比较。结果表明,该方法在不同信道和信噪比条件下都具有较好的鲁棒性。
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