数字调制解调器中有效的近最优最大似然符号时序恢复

V. Tuukkanen, J. Vesma, M. Renfors
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引用次数: 5

摘要

最大似然估计理论为开发数字通信系统的最佳定时恢复方案提供了一个通用框架。基于机器学习理论的前馈方案具有快速获取的特点。另一个重要的趋势是使用数字插值进行符号时序调整。所谓的Farrow(1988)结构在这种情况下变得流行,因为它为这样的插值任务提供了有效和灵活的实现结构。在之前的一篇论文中,Vesma和Tuukkanen(参见Proc. IEEE NORSIG 96, Espoo, Finland, p.183-6, 1997)提出了一种新的前馈时序估计方案,该方案有效地利用了Farrow结构。该方案基于对数似然函数的低阶多项式近似,并且该函数的导数可以以很小的额外计算成本获得。在移动通信系统中,即使在较短的码块长度下,该定时恢复技术的性能也接近理想。在本文中,我们证明了当使用优化的训练序列时,这种新方案可以获得更好的结果。该方案也适用于严重多径失真信道。
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Efficient near optimal maximum likelihood symbol timing recovery in digital modems
Maximum likelihood (ML) estimation theory provides a general framework for developing optimum timing recovery schemes for digital communication systems. Feedforward schemes based on ML-theory have been shown to have rapid acquisition characteristics. Another important trend is to use digital interpolation for symbol timing adjustment. The so-called Farrow (1988) structure has become popular in this context because it offers an efficient and flexible realization structure for such an interpolation task. In a previous paper Vesma and Tuukkanen (see Proc. IEEE NORSIG 96, Espoo, Finland, p.183-6, 1997) proposed a new feedforward timing estimation scheme which utilizes the Farrow structure efficiently. The scheme is based on a low-order polynomial approximation for the log-likelihood function and also the derivative of this function is available with a small additional computational cost. The performance of the new timing recovery technique was found to be close to ideal even with short symbol block-lengths which is very important in mobile systems. In this paper, we show that this new scheme gives much better results when optimized training sequences are used. The scheme works also with severe multipath distortion channel.
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