The Channel Compressive Sensing Estimation for Power Line Based on OMP Algorithm

Joint Authors

Liang, Kun
He, Yeshen
Wu, Yannian
Hu, Xin
Sun, Lili
Li, Xiangzhen

Source

Journal of Electrical and Computer Engineering

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-04-23

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Information Technology and Computer Science

Abstract EN

Power line communication (PLC) can collect information by power line which increases the coverage and connectivity of the smart grid.

In this paper, we analyze the transmission characteristics of the power line channel and model it with mathematics channel.

The multipath effect of the power line channel is studied with a novel technology named compressive sensing herein.

We also proposed a new method to the power line channel estimation based on compressive sensing.

We can collect and extract the effective parameters of the power line channel to storage, which only take very little storage space.

The simulation results show that the proposed approach can reduce the amount of processing data in the digital signal processing module and decrease the requirement for the hardware.

American Psychological Association (APA)

Li, Xiangzhen& Liang, Kun& He, Yeshen& Wu, Yannian& Hu, Xin& Sun, Lili. 2017. The Channel Compressive Sensing Estimation for Power Line Based on OMP Algorithm. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1175240

Modern Language Association (MLA)

Li, Xiangzhen…[et al.]. The Channel Compressive Sensing Estimation for Power Line Based on OMP Algorithm. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1175240

American Medical Association (AMA)

Li, Xiangzhen& Liang, Kun& He, Yeshen& Wu, Yannian& Hu, Xin& Sun, Lili. The Channel Compressive Sensing Estimation for Power Line Based on OMP Algorithm. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1175240

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1175240