【作者】 陈学军；

【导师】 骆源；

【作者基本信息】 上海交通大学 ， 计算机技术（专业学位）， 2016， 硕士

【摘要】 随着中国移动互联网技术的发展,LTE技术已经成为现阶段研究的热点。正交频分复用(OFDM)作为LTE的核心技术,具有高速率的数据传输,并且能够有效地克服信道频率选择性衰落,已经被应用到了生活的各个方面。然而,无线信道的多径效应导致OFDM信号前后相邻符号相互叠加,错误的OFDM符号定时同步会导致FFT处理窗包含连续的两个OFDM符号的值,带来符号间干扰(ISI)以及子载波间干扰(ICI),OFDM系统的性能受到严重影响。对OFDM系统的多径衰落信道进行时延估计,能够应用到符号定时同步和干扰消除等各个方面。首先,本文研究了OFDM系统的基本原理以及多径衰落信道的数学模型。在此信道模型上,对一些经典的盲时延估计算法进行了研究。过去的算法一般是通过计算接收信号符号的每一位与其后面第N位采样点的相关程度来判断多径时延,如Karthik的算法利用余弦值计算相关系数,因此复杂度较高。接着,本文提出了一种低复杂度的盲时延估计算法,并获得HMWC2014最佳学生论文奖。该算法将向量间的曼哈顿距离作为相关系数来估计多径时延,乘法运算复杂度从多项式时间降到了零,因此复杂度降低。相比于余弦值法计算向量间的夹角,曼哈顿距离通过计算向量的差值来获得相关系数,具有更高的精度。仿真结果也验证了该算法在准确性方面有较好的性能。最后本文建立了阈值对估计误差影响的数学模型,通过理论分析得出最优阈值很难获得,并提出了一种基于L1范式的次优阈值的选择方法,有效地提高了算法的准确性。更多还原

【Abstract】 With the development of China mobile Internet technology,LTE technology has become a research hotspot in current stage.As the core technology of the LTE,Orthogonal Frequency Division Multiplexing(OFDM),which has a high data transmission rate,can effectively overcome the frequency selection in multipath fading channels and has been applied to many aspects of people’s life.However,adjacent symbols may be overlapping because of the multipath effect.In this case,OFDM symbol timing synchronization error would lead to the wrong position of the FFT processing window.One window would contain the values of two consecutive OFDM symbols,which brings the InterSymbol Interference(ISI)and InterCarrier Interference(ICI)and largely influences the performance of OFDM systems.As a solution to the problem,multipath delay-spread estimation in OFDM system can be applied to the symbol timing recovery,interference elimination and so on.This paper proposes a low complexity delay-spread estimation algorithm in OFDM system under multipath fading channels.Firstly,the paper presents the basic principle of OFDM system and the mathematical model of the multipath fading channels.Based on the channel model,we reviews several typical blind delay-spread estimation algorithms.Generally those algorithms calculate the correlation of each sample in the received signal symbols with its N-th later sample to estimate the delay-spread.For example,Karthik’s algorithm uses the cosine similarity as the correlator and the complexity is high.Then,we propose a new blind delay-spread estimation algorithm with low computational complexity,which won the best student paper award in HMWC 2014.It uses the Manhattan distance to calculate the correlation of samples to estimate the multipath delay-spread.The computational complexity for multiplication is reduced from polynomial time to zero,so the whole complexity is greatly reduced.Compared with the cosine similarity,which is used for calculating the angle between two vectors,Manhattan distance obtains the correlation by calculating the difference between two vectors,hence it has a higher precision.The simulation results verify that our algorithm has better performance in accuracy than Karthik’s.In the end,this paper establishes a mathematical model of the threshold’s effect on estimation error,theoretically illustrates the difficulty to obtain the optimal threshold and proposes an algorithm to obtain the suboptimal threshold based on L1-norm.It effectively improves the accuracy of our algorithm.更多还原