Loading [MathJax]/extensions/MathMenu.js
Clipping Noise Cancelation for OFDM Systems Using Reliable Observations Based on Compressed Sensing | IEEE Journals & Magazine | IEEE Xplore

Clipping Noise Cancelation for OFDM Systems Using Reliable Observations Based on Compressed Sensing


Abstract:

In this paper, a clipping noise cancelation scheme using compressed sensing (CS) technique is proposed for orthogonal frequency division multiplexing systems. The propose...Show More

Abstract:

In this paper, a clipping noise cancelation scheme using compressed sensing (CS) technique is proposed for orthogonal frequency division multiplexing systems. The proposed scheme does not need reserved tones or pilot tones, which is different from the previous works using CS technique. Instead, observations of the clipping noise in data tones are exploited, which leads to no loss of data rate. Also, in contrast with the previous works, the proposed scheme selectively exploits the reliable observations of the clipping noise instead of using whole observations, which results in minimizing the bad influence of channel noise. From the selected reliable observations, the clipping noise in time domain is reconstructed and canceled by using CS technique. Simulation results show that the proposed scheme performs well compared to other conventional clipping noise cancelation schemes and shows the best performance in some cases.
Published in: IEEE Transactions on Broadcasting ( Volume: 61, Issue: 1, March 2015)
Page(s): 111 - 118
Date of Publication: 18 December 2014

ISSN Information:

No metrics found for this document.

I. Introduction

Orthogonal frequency division multiplexing (OFDM) is known as one of the best modulation schemes for high-rate data transmission in wireless communications due to its robustness against multipath fading, bandwidth efficiency, and simple implementation. However, due to high peak-to-average power ratio (PAPR) of an OFDM signal, OFDM systems require expensive high power amplifiers having a large dynamic range.

Usage
Select a Year
2025

View as

Total usage sinceDec 2014:930
012345JanFebMarAprMayJunJulAugSepOctNovDec430000000000
Year Total:7
Data is updated monthly. Usage includes PDF downloads and HTML views.
Contact IEEE to Subscribe

References

References is not available for this document.