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基于二次差分概率的无线信道估计方法
Radio channel estimation method based on quadratic differentials probability
- 电信科学 2017年33卷第1期 页码：34-44
- 作者机构：
- 作者简介：
[ "王立姣（1990-），女，大连工业大学硕士生，主要研究方向为通信与物联网。" ]
[ "杜薇薇（1994-），女，大连工业大学硕士生，主要研究方向为通信与物联网。" ]
[ "李凡（1992-），女，大连工业大学硕士生，主要研究方向为通信与物联网。" ]
[ "王智森（1963-），男，博士，大连工业大学信息科学与工程学院院长、教授，集成测控技术研究所所长，主要研究方向为无线通信与网络、数字信号处理、物联理论与物联技术。" ]
- 基金信息：
DOI：10.11959/j.issn.1000-0801.2017015
中图分类号： TN929.5-
网络出版日期：2017-01，
纸质出版日期：2017-01-15
- 稿件说明：
移动端阅览
王立姣, 杜薇薇, 李凡, 等. 基于二次差分概率的无线信道估计方法[J]. 电信科学, 2017,33(1):34-44.
Lijiao WANG, Weiwei DU, Fan LI, et al. Radio channel estimation method based on quadratic differentials probability[J]. Telecommunications science, 2017, 33(1): 34-44.
王立姣, 杜薇薇, 李凡, 等. 基于二次差分概率的无线信道估计方法[J]. 电信科学, 2017,33(1):34-44. DOI： 10.11959/j.issn.1000-0801.2017015.
Lijiao WANG, Weiwei DU, Fan LI, et al. Radio channel estimation method based on quadratic differentials probability[J]. Telecommunications science, 2017, 33(1): 34-44. DOI： 10.11959/j.issn.1000-0801.2017015.
摘要
5G具有高速率和大带宽的特性，使得无线信号在时域和频域的衰落更加明显。随着差分值统计步长和空间采样间隔的增大，采用差分概率信道估计方法已无法跟踪深衰落区域，且峰值区域跟踪过度。针对以上问题提出一种二次差分概率的信道估计方法。该方法首先找到衰落曲线的谷值点和峰值点，然后通过二次差分概率对深衰落区域和峰值区域的估计差分值进行改善，最后利用差分运算得到估计增益。仿真实验结果表明，此方法有效地提高了整体的跟踪性能，并降低了跟踪误差。
Abstract
The fifth generation (5G) mobile communication technology has the characteristics of high speed and large bandwidth
which makes the fading of radio signal in time domain and frequency domain more obviously.With the increase of differential values statistical step and the spatial sampling interval
the channel estimation method based on the differential probability can't track the deep fading area and the peak area was over-tacked.In view of the above problems
a channel estimation method based on quadratic differentials probability was proposed.Firstly
the valley point and peak point of the fading curve were found.Then
the estimated differential values of deep fading area and peak area were improved by quadratic differential probability.Finally
the estimated gains were obtained by the difference operation.Simulation results show that
this method can improve the whole tracking performance effectively and reduce the tracking error.
关键词
Keywords
references
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