This work establishes the design, analysis, and fine-tuning of a peak-to-average-power-ratio (PAPR) reducing system, based on compressed sensing (CS) at the receiver of a peak-reducing sparse clipper applied to an orthogonal frequency-division multiplexing (OFDM) signal at the transmitter. By exploiting the sparsity of clipping events in the time domain relative to a predefined clipping threshold, the method depends on partially observing the frequency content of the clipping distortion over reserved tones to estimate the remaining distortion. The approach has the advantage of eliminating the computational complexity at the transmitter and reducing the overall complexity of the system compared to previous methods which incorporate pilots to cancel nonlinear distortion. Data-based augmented CS methods are also proposed that draw upon available phase and support information from data tones for enhanced estimation and cancelation of clipping noise. This enables signal recovery under more severe clipping scenarios and hence lower PAPR can be achieved compared to conventional CS techniques. © 2012 IEEE.
|Original language||English (US)|
|Number of pages||6|
|Journal||IEEE Transactions on Signal Processing|
|State||Published - Jul 2012|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors would like to acknowledge the support provided by the Deanship of Scientific Research at King Fahd University of Petroleum & Minerals (KFUPM) under Research Grant FT100030.
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering