一种低开销的LTE上行链路信道估计算法

压缩感知理论作为信号处理方向较为前沿的研究方向,可以采用少数目的采样值以高概率来获得原始稀疏信号。同时,移动无线通信衰落信道恰恰具有稀疏特性。然而,传统的信道估计并没有根据信道的这一稀疏特性来得出算法。在研究多径信道稀疏特性的基础上,分析了将压缩感知理论运用于LTE上行链路进行信道估计的可行性,并建立了一种基于压缩感知技术实现系统信道估计的模型,提出了一种结合正交匹配追踪算法来估计信道时域响应的低开销LTE上行链路信道估计算法。此外,通过系统仿真进行了估计的均方误差性能分析,与目前广为使用的信道估计算法相比,所提出的低开销信道估计算法在保证估计精度的同时减少了导频开销,增强了系统性能。

A Low-overhead Channel Estimation Algorithm for LTE Uplink

As the latest research achievement in signal processing field, compress sensing theory implements to reconstruction sparse signal by little sampled values with high probability. At the same time, radio communication channel has the characteristic of sparsity. The traditional channel estimation algorithms do not take advantage of it. The thesis attempts to apply compress sensing theory to channel estimation for LTE uplink. After its feasibility proved by theory, the effectiveness is confirmed by simulation. A channel estimation model based on compress sensing is presented, and an algorithm with Orthogonal Matching Pursuit to get channel time domain impulse is proposed. Compared with the traditional channel estimation algorithms, the proposed method with low-overhead has the advantages of less pilot numbers, better bandwidth efficiency in the premise of the same precise estimation by simulation.