2008
DOI: 10.1109/vetecs.2008.205
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Iterative Correction of Clipped and Filtered Spatially Multiplexed OFDM Signals

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Cited by 7 publications
(10 citation statements)
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“…There have been several iterative techniques that were introduced to reduce the nonlinear distortions due to clipping at the receiver end 2–10. A maximum likelihood (ML) decision based nonlinear (i.e., clipping) noise reduction for multi‐carrier signals (i.e., OFDM) was proposed in Reference 2 while taking into consideration the clipping noise at the receiver over a Gaussian channel (thus, channel equalizer was not considered).…”
Section: Introductionmentioning
confidence: 99%
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“…There have been several iterative techniques that were introduced to reduce the nonlinear distortions due to clipping at the receiver end 2–10. A maximum likelihood (ML) decision based nonlinear (i.e., clipping) noise reduction for multi‐carrier signals (i.e., OFDM) was proposed in Reference 2 while taking into consideration the clipping noise at the receiver over a Gaussian channel (thus, channel equalizer was not considered).…”
Section: Introductionmentioning
confidence: 99%
“…Clipping noise reduction and cancelation technique based on DAR algorithm was proposed in Reference 5. Iterative reduction of clipping noise was presented in Reference 6 as an extension of Reference 4 to multiple‐input multiple‐output (MIMO) OFDM based on perfect knowledge of CSI, where the authors use a complex computation of clipping noise estimate using sub‐optimal linear minimum mean square error (LMMSE) filtering based on the iterative algorithm given in Reference 5. The knowledge of noise and distortion variance is required a priori to compute the weight of LMMSE filter, which requires an update of noise and distortion variance during each iteration.…”
Section: Introductionmentioning
confidence: 99%
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