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Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

机译:PRML系统的接近最小误码率均衡器自适应

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Receivers for partial response maximum-likelihood systems typically use a linear equalizer followed by a Viterbi detector. The equalizer tries to confine the channel intersymbol interferenceto a short span in order to limit the implementation complexity of the Viterbi detector. Equalization is usually made adaptive in order to compensate for channel variations. Conventional adaptation techniques, e.g., LMS, are, in general, suboptimal in terms of bit-error rate (BER). In this paper, we present a new equalizer adaptation algorithm that seeks to minimize the BER at the Viterbi detector output. The algorithm extracts information from the sequenced amplitude margin (SAM) histogram and incorporates a selection mechanism that focuses adaptation on particular data and noise realizations. The selection mechanism is based on the reliability of the add compare select (ACS) operations in the Viterbi detector. From a complexity standpoint, the algorithm is essentially as simple as the conventional LMS algorithm. Moreover, we present a further simplified version of the algorithm that does not require any hardware multiplications. Simulation results, for an idealized optical storage channel, confirm a substantial performance improvement relative to existing adaptation algorithms.
机译:用于部分响应最大似然系统的接收器通常使用线性均衡器,然后使用维特比检测器。均衡器试图将信道符号间干扰限制在较短的范围内,以限制维特比检测器的实现复杂性。通常均衡是自适应的,以补偿信道变化。就比特误码率(BER)而言,常规的自适应技术,例如LMS,通常是次优的。在本文中,我们提出了一种新的均衡器自适应算法,旨在最小化Viterbi检测器输出的BER。该算法从序列幅度裕度(SAM)直方图中提取信息,并结合了选择机制,该机制将适应重点放在特定数据和噪声实现上。选择机制基于维特比检测器中加比较选择(ACS)操作的可靠性。从复杂性的角度来看,该算法本质上与常规LMS算法一样简单。此外,我们提出了该算法的进一步简化版本,不需要任何硬件乘法。对于理想的光存储通道,仿真结果证实了相对于现有自适应算法的显着性能提升。

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