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Block synchronisation for joint channel and DC-offset estimation using data-dependent superimposed training

机译:使用依赖于数据的叠加训练来阻止联合信道和DC偏移估计的同步

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摘要

In this paper, we propose a new (single-step) block synchronisation algorithm for joint channel and DC-offset estimation for data-dependent superimposed training (DDST). While a (two-step) block synchronisation algorithm for DDST has previously been proposed in [5], due to interference from the information-bearing data it performed sub-optimally, resulting in channel estimates with unknown delays. These delay ambiguities (also present in the equaliser) were then estimated in [5] in a non-practical manner. In this paper we avoid the need for estimation of this delay ambiguity by exploiting the special structure of the channel output’s cyclic mean vector. The result is a BER performance superior to the DDST synchronisation algorithm first published in [5].
机译:在本文中,我们提出了一种新的(单步)块同步算法,用于联合通道和DC偏移估计,用于数据相关的叠加训练(DDST)。尽管先前在[5]中提出了一种针对DDST的(两步)块同步算法,但由于受到信息承载数据的干扰,该算法次优执行,从而导致信道估计具有未知延迟。然后以非实用的方式在[5]中估算这些延迟模糊度(也存在于均衡器中)。在本文中,我们通过利用通道输出的循环平均矢量的特殊结构,避免了对此延迟歧义进行估计的需要。结果是BER性能优于[5]中首次发布的DDST同步算法。

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