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dc.contributor.authorAl-Safadi, Ebrahim B.
dc.contributor.authorAl-Naffouri, Tareq Y.
dc.date.accessioned2015-08-03T09:57:20Z
dc.date.available2015-08-03T09:57:20Z
dc.date.issued2012-07
dc.identifier.issn1053587X
dc.identifier.doi10.1109/TSP.2012.2193396
dc.identifier.urihttp://hdl.handle.net/10754/562232
dc.description.abstractThis 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.
dc.description.sponsorshipThe 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.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://arxiv.org/abs/arXiv:1101.4335v1
dc.subjectCompressive sensing
dc.subjectPAPR reduction
dc.subjectsparse signal estimation
dc.subjecttone reservation techniques
dc.titlePeak reduction and clipping mitigation in OFDM by augmented compressive sensing
dc.typeArticle
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journalIEEE Transactions on Signal Processing
dc.contributor.institutionElectrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), 31261 Dhahran, Saudi Arabia
dc.identifier.arxividarXiv:1101.4335
kaust.personAl-Naffouri, Tareq Y.


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