| 摘要: |
| 粒子滤波可以用来处理非线性非高斯问题,而序列重要性重采样算法能较好地解决粒子滤波中的粒子退化问题,由此将序列重要性重采样算法运用于MIMO时变信道进行半盲估计.实验结果表明:与使用传统的粒子滤波方法相比,基于序列重要性重采样算法的MIMO时变信道半盲估计方法均方误差和误码率降低,从而改善了接收端的符号检测性能. |
| 关键词: 序列重要性重采样算法 MIMO时变信道 半盲估计 粒子滤波 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金项目(61101209);上海市自然科学基金项目(11ZR1426600) |
|
| Semiblind estimation of MIMO time－varying channels based on sequential importance resampling algorithm |
|
SHI Danfeng, ZHANG Jing
|
|
College of Information,Mechanical and Electrical Engineering,Shanghai Normal University
|
| Abstract: |
| Particle filtering can be used to handle the non－liner and non－Gaussian problems,while the sequential importance resampling (SIR) algorithm can be better to solve the degeneracy phenomenon in particle filtering and be applied in the semiblind estimation of MIMO time－varying channels.Simulation results show that compared to traditional particle filtering method,the MIMO time－varying channel semiblind estimation method based on the sequential importance resampling algorithm reduces the Mean square error and Symbol error rate,consequently improves the symbol detection performance at the receiver side. |
| Key words: the sequential importance resampling algorithm MIMO time－varying channels semiblind estimation particle filtering |
Editorial Board