Designing tone reservation PAR reduction
EURASIP Journal on Applied Signal Processing
New algorithms for blind recognition of OFDM based systems
Signal Processing
On reducing the complexity of tone-reservation based PAPR reduction schemes by compressive sensing
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
IEEE Transactions on Circuits and Systems II: Express Briefs
Digital post-processing for reducing A/D converter nonlinear distortion in wideband radio receivers
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
A model reduction approach for OFDM channel estimation under high mobility conditions
IEEE Transactions on Signal Processing
Adaptive algorithms for sparse system identification
Signal Processing
Compressed sensing of complex-valued data
Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
An active-set approach for OFDM PAR reduction via tone reservation
IEEE Transactions on Signal Processing
Journal of Electrical and Computer Engineering
A New Peak-to-Average Power-Ratio Reduction Algorithm for OFDM Systems via Constellation Extension
IEEE Transactions on Wireless Communications
On the Nonlinear Companding Transform for Reduction in PAPR of MCM Signals
IEEE Transactions on Wireless Communications
Just relax: convex programming methods for identifying sparse signals in noise
IEEE Transactions on Information Theory
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
IEEE Transactions on Information Theory
Highly Robust Error Correction byConvex Programming
IEEE Transactions on Information Theory
Block coded modulation for the reduction of the peak to average power ratio in OFDM systems
IEEE Transactions on Consumer Electronics
Complement block coding for reduction in peak-to-average power ratio of OFDM signals
IEEE Communications Magazine
IEEE Journal on Selected Areas in Communications
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In this paper, compressed sensing techniques are proposed to linearize commercial power amplifiers driven by orthogonal frequency division multiplexing signals. The nonlinear distortion is considered as a sparse phenomenon in the time-domain, and three compressed sensing based algorithms are presented to estimate and compensate for these distortions at the receiver using a few and, at times, even no frequency-domain free carriers (i.e. pilot carriers). The first technique is a conventional compressed sensing approach, while the second incorporates a priori information about the distortions to enhance the estimation. Finally, the third technique involves an iterative data-aided algorithm that does not require any pilot carriers and hence allows the system to work at maximum bandwidth efficiency. The performances of all the proposed techniques are evaluated on a commercial power amplifier and compared. The error vector magnitude and symbol error rate results show the ability of compressed sensing to compensate for the amplifier's nonlinear distortions.