基于循环平稳的LOFDM系统双散射信道最大多普勒扩展盲估计

Cyclostationarity-Based Maximal Doppler Spread Blind Estimation for LOFDM Systems in Doubly-Dispersive Channels

  • 摘要: Strohmer T与Beaver S于2003年提出了适用于时频散射信道的网格正交频分复用 (LOFDM, Lattice Orthogonal Frequency Division Multiplexing)系统,与传统OFDM系统相比该系统具有更高的频带利用率和更好的误码性能。LOFDM系统发送端需要自适应地调整信号的原形脉冲和其时频分布的参数与信道保持匹配,以尽可能地降低符号间干扰和载波间干扰的影响。最大多普勒扩展作为信道时变性的直接反映,是LOFDM系统自适应策略的重要参数之一。本文针对LOFDM系统的信号特性,提出了一种双散射信道条件下基于循环平稳的LOFDM系统最大多普勒扩展盲估计算法,克服了现有估计算法存在频谱效率浪费的不足。理论分析与计算机仿真表明:算法可在信道多径信息未知的情况下实现较大取值范围的多普勒扩展的有效估计,具有良好的归一化均方误差性能,且抗噪声能力较强、收敛速度较快。

     

    Abstract: LOFDM (Lattice Orthogonal Frequency Division Multiplexing), which is proposed by Strohmer T and Beaver S in 2003, has higher spectral efficiency and better bit error rate (BER) performance compared with OFDM systems in the time-frequency dispersive channel. To minimize the joint inter-symbol interference (ISI) and inter-carrier interference (ICI) caused by the doubly dispersive channel, LOFDM systems need to adapt the parameters of signals’ TFL and shaping-pulse scale to the channel dispersion characteristics in the transmitters. The maximal Doppler spread, or equivalently, the mobile speed, is a measure of the spectral dispersion of mobile fading channel. Accurate estimation of the mobile speed is of importance in LOFDM systems which require the knowledge of the rate of channel variations to achieve its adaptive strategy. In this paper, aiming at the special characteristics of LOFDM signals, a cyclostationarity-based blind maximal Doppler spread estimation algorithm for LOFDM systems over the doubly-dispersion channels is proposed, which avoids the waste of spectral efficiency in the current estimation algorithms. Theory analyses and simulation results demonstrate that the proposed algorithm can obtain the effective estimation for a wide range of Doppler spreads under the condition that the information of the multi-path is unknown and have a good normalized mean square error (NMSE) performance, while both the capability of anti-noise and the speed of convergence are nice.

     

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