基于压缩感知的同频干扰下LTE系统信道估计算法

Compressive Sensing Based Channel Estimation for LTE System in the Presence of Co-channel Interferences

  • 摘要: 本文提出一种基于压缩感知的同频干扰下长期演进系统信道估计方法。与现有方法不同,本文将干扰和噪声区别对待,利用干扰信号结构建立该系统下多小区信道估计模型(MCCE)。由于无线信道在宽带系统下表现出较为明显的稀疏特性,本文将压缩感知技术应用于上述模型,通过求解新的感知矩阵,并利用多输入多输出信道共有非零支撑集的特性,提出了适用于长期演进系统的联合改进子空间追踪算法(J-MSP),解决了上述模型下字典矩阵列相关度较高的问题;由于所提模型中含有未知的干扰符号,因此还需解决信道和干扰符号的联合估计。仿真结果和分析表明,本文方法在干扰与本小区同步时相比单小区信道估计方法性能显著提升,异步时与最大似然算法性能相当,同时也适用于无干扰场景。

     

    Abstract: In this paper, we consider the Long Term Evolution (LTE) system in the presence of co-channel interferences (CCIs) and a channel estimation method based on compressive sensing is proposed. Compared to the existing work on the interfered channel estimation, we make use of interferes’ signal structure which is distinguished with the Gaussians noise, a model of multi-cell channel estimation (MCCE) is set up. Promoted by the sparseness of wireless channel in the wideband system like Long Term Evolution, we develop the Joint Modified Subspace Pursuit (J-MSP) algorithm which designs new sensing matrix to overcome column highly coherent problem in the channel estimation formulation and exploits the multi-input multi-output (MIMO) channel sharing common support characteristic based on the existing Subspace Pursuit (SP) within the compressive sensing framework. After the joint estimation of channel and unknown interference symbols, the channel estimation can be obtained by using the multi-cell model. Simulations and analysis show that the proposed method I) outperforms single-cell channel estimation method greatly when there is synchronous interference; II) is comparable to Maximum Likelihood Estimator (MLE) in case of asynchronous interference; III) can also be applied to the noise-only scenario.

     

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