摘要
传统基于压缩感知的信道估计方法存在计算复杂度较高、较难应用于实际的问题。为此,将广义的正交匹配追踪(GOMP)算法应用到信道估计中,通过一次迭代选取多个原子,降低算法的计算复杂度,考虑无线信道的能量分布特征,提出一种基于分级回归追踪的GOMP算法。该算法采取分级的方法选择原子,利用回归追踪的方法去除非匹配原子,从而保证原子的快速准确选择。实验结果表明,该算法在保证信道估计精度的同时,可有效地降低计算复杂度,具有较好的鲁棒性。
Traditional Compressed Sensing （CS ）based channel estimation methods are difficult to implement due to their high computational complexity.To solve this problem,Generalized Orthogonal Matching Pursuit（GOMP）algorithm is used for channel estimation,which reduces computational complexity by selecting multiple indices in each iteration. Considering the power distribution of wireless channel,a classifying-back-tracing based Generalized Orthogonal Matching Pursuit（Cbt-GOMP）algorithm is proposed.This algorithm utilizes classification to select atoms and takes advantage of back-tracing to remove non-matching atoms,which guarantee a fast and accurate atom selecting.Simulation results show that this algorithm can not only guarantee channel estimation accuracy,but also reduce computational complexity effectively.Additionally,this method also has good robustness.
出处
《计算机工程》
CAS
CSCD
北大核心
2016年第11期120-124,130,共6页
Computer Engineering
基金
国家自然科学基金(61471077
61301126)
重庆市基础与前沿研究计划一般项目(cstc2013jcyj A40034
cstc2013jcyj A40041)
重庆市教委科学技术研究项目(KJ1400413)
关键词
信道估计
压缩感知
计算复杂度
导频
匹配原子
channel estimation
Compressed Sensing （ CS ）
computational complexity
pilot
matching atom
