物理层网络编码的符号时钟估计

现有的关于物理层网络编码(PNC)的研究多建立在时钟已完全同步的基础上，对PNC的符号时钟同步研究较少。而实际上符号时钟在PNC中是必不可少的。针对这一问题，该文提出一种新的基于正交训练序列适用于双向中继信道PNC的符号时钟估计方法。该方法根据最大似然估计准则，运用基于离散傅里叶变换(DFT)的插值算法来估计时钟误差。仿真结果表明，所提出的DFT插值算法性能优越，在信噪比(SNR)大于10 dB的条件下，系统的均方误差(MSE)性能比经典优选采样点法提升1个数量级，并且非常逼近修正克拉美罗界(MCRB)。

Symbol Timing Estimation for Physical-layer Network Coding

Most of the existing research on Physical-layer Network Coding (PNC) is based on the assumption that the symbol timing at the relay is ideally synchronized, and rarely discusses the issue of symbol synchronization. However, in practice, the symbol timing is indispensable in PNC systems. To tackle this problem, this paper proposes a novel symbol timing estimation scheme based on the orthogonal training sequences for PNC in two-way relay channels. According to the maximum-likelihood estimation criterion, a Discrete Fourier Transformation (DFT) based interpolation algorithm is applied to improve the estimation accuracy. It is shown by analysis and simulation that the proposed DFT-based symbol timing estimator exhibits superior performance. The Mean Square Error (MSE) performance of the estimator is one order of magnitude better than that of the conventional optimum sample algorithm for Signal-to-Noise Ratio (SNR) greater than 10 dB, and is very close to the Modified Cramer-Rao Bound (MCRB).