上行MIMO-OFDM系统中基于改进GAIC算法的稀疏信道估计

Sparse Channel Estimation Based on Improved GAIC Algorithm in Uplink MIMO-OFDM System

大量实验证据和物理论证表明,无线信道中的信号传输呈现系统的多径稀疏结构,并随着信号空间维度变大愈加明显,而现有大多数信道估计算法均未在复杂度与准确的稀疏信道估计之间实现平衡。根据大规模MIMO(multiple-input multiple-output)系统固有的稀疏特性,提出基于改进广义Akaike信息准则(GAIC)的具有低矩阵运算量的信道估计算法。该算法根据有效抽头处脉冲幅度值较大特点,利用代价函数获取有效抽头位置准确执行信道估计,最大程度地降低噪声干扰。仿真表明该算法具有良好的抗噪性能和抗多径干扰能力。

At this stage,a large number of experimental evidence and physical evidence show that,in practice,signal transmission in many wireless channels tends to present a systematic multipath sparse structure,and becomes apparent as the spatial dimension of the signal becomes larger,while most existing channel estimation algorithms fail to provide a good compromise between complexity and accurate sparse channel estimation.This paper proposes a channel estimation algorithm based on the improved generalized akaike information criterion (GAIC) algorithm based on the sparse nature of multiple-input multiple-output systems.The algorithm has a large pulse amplitude at the effective tap and it makes use of cost function to obtain effective tap position to accurately perform channel estimation and minimize the noise interference.Simulation results show that the algorithm can have good anti-noise performance and resistance to multi-path interference.