TY - JOUR
T1 - Compressed sensing techniques for receiver based post-compensation of transmitter's nonlinear distortions in OFDM systems
AU - Owodunni, Damilola S.
AU - Ali, Anum Z.
AU - Quadeer, Ahmed Abdul
AU - Al-Safadi, Ebrahim B.
AU - Hammi, Oualid
AU - Al-Naffouri, Tareq Y.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported by King Abdulaziz City for Science and Technology (KACST) through the Science & Technology Unit at King Fahd University of Petroleum & Minerals through Project no. 11-ELE1651-04 as part of the National Science, Technology and Innovation Plan.
PY - 2014/4
Y1 - 2014/4
N2 - 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. © 2013 Elsevier B.V.
AB - 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. © 2013 Elsevier B.V.
UR - http://hdl.handle.net/10754/563463
UR - https://linkinghub.elsevier.com/retrieve/pii/S0165168413004209
UR - http://www.scopus.com/inward/record.url?scp=84889662457&partnerID=8YFLogxK
U2 - 10.1016/j.sigpro.2013.10.029
DO - 10.1016/j.sigpro.2013.10.029
M3 - Article
SN - 0165-1684
VL - 97
SP - 282
EP - 293
JO - Signal Processing
JF - Signal Processing
ER -