相关性增强的OFDM粗同步序列分析与设计

Analysis and Design of Correlation-Enhanced Preamble for OFDM Coarse Synchronization

  • 摘要: 正交频分复用技术(Orthogonal frequency-division multiplexing, OFDM)在通信领域被广泛应用, OFDM信号在接收时要求子载波严格正交,同步精度对传输效果影响很大,因此OFDM信号同步始终是该领域的一个研究重点。首先,包含同步序列的同步算法可分为自相关和互相关两类,文章分析了各类算法的特点,尤其针对S&C、Minn、Park、Ren四种经典自相关算法和Two-Stage算法的优势和局限做出详细讨论,并比较了上述算法的理论公式复杂度与迭代计算复杂度。其次,本文设计了一种自相关同步序列结构以及对应的度量函数和频偏估计算法;其核心原理是在同步序列间引入相关性,增大计算度量函数时引入的数据点数,通过提高计算复杂度提高同步精度,尽量避免度量函数出现副峰;该算法还保留了迭代计算的特性,便于硬件实现。最后,在比较提出算法和其他经典算法的同步效果时,用度量函数最大值落在接收信号保护间隔内的概率刻画定时准确度,用归一化频偏的均方误差(Mean square error,MSE)刻画频偏估计精度。仿真结果表明,在加性高斯白噪声(Additive white Gaussian noise,AWGN)信道和两径信道下,算法的定时准确度优于其他经典自相关算法,与Two-Stage算法接近,但是复杂度比前者低。此外,得益于提出算法在低信噪比下较高的定时准确度,其在AWGN信道下的频偏估计精度优于其他经典自相关算法;在两径信道下,以20 dB为界,信噪比在20 dB以下时提出算法的频偏估计精度更高。

     

    Abstract: ‍ ‍Orthogonal frequency-division multiplexing (OFDM) technology is widely used in the communications field. Since OFDM requires orthogonal subcarriers, the synchronization accuracy greatly affects the transmission quality. Therefore, synchronization for OFDM has been a key research point in communications. First, synchronization with preambles can be divided into two categories: autocorrelation and cross-correlation. This paper analyzes the characteristics of autocorrelation and cross-correlation synchronization methods. In particular, the distributions and limitations of the four classic autocorrelation methods from S&C, Minn, Park, and Ren, and another Two-Stage approach are discussed. The complexity of the theoretical formula and the iterative calculation complexity of the above algorithms are also compared. On this basis, correlation-enhanced timing and frequency synchronization for OFDM are proposed, including the preamble, matched timing metric, and method of carrier frequency offset estimation. The main idea is to introduce correlation among preambles, increase the amount of data samples when calculating, and avoid side peaks in the timing metric. The accuracy of our synchronization method is improved by increasing the computational complexity. In addition, the timing synchronization method supports iterative calculation and facilitates hardware implementation. When comparing the performance of different methods, the accuracy of timing synchronization is estimated by the probability that the maximum value of the timing metric falls within the guard interval of the received signal. The accuracy of frequency offset estimation is expressed by the mean square error (MSE) of the normalized frequency offset. The simulation results show that the accuracy of timing synchronization is better than other classic autocorrelation methods and is close to that of the two-stage approach under the additive white Gaussian noise (AWGN) channel and the two-path channel, but the complexity of the proposed method is less than that of the Two-Stage approach. Furthermore, owing to the higher accuracy of timing synchronization, the performance of the proposed frequency offset estimation under the AWGN channel is better than other classic autocorrelation methods. With 20 dB as the boundary under a two-path channel, the performance of the proposed frequency offset estimation is better when the signal-to-noise ratio is below 20 dB.

     

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