2010
DOI: 10.1504/ijista.2010.036586
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Digital feedforward compensation scheme for the non-linear power amplifier with memory

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Cited by 4 publications
(14 citation statements)
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“…For arbitrary and , the output of the linearizer can be rewritten as (19) where and . Then the IMD suppression at the linearizer output is IMD (20) Note that only the accuracy of determines the amount of IMD suppression which was the case for memoryless nonlinearity as well.…”
Section: Basic Operation Under Wiener-hammerstein Memorymentioning
confidence: 99%
See 3 more Smart Citations
“…For arbitrary and , the output of the linearizer can be rewritten as (19) where and . Then the IMD suppression at the linearizer output is IMD (20) Note that only the accuracy of determines the amount of IMD suppression which was the case for memoryless nonlinearity as well.…”
Section: Basic Operation Under Wiener-hammerstein Memorymentioning
confidence: 99%
“…Gradient based learning methods implemented either digitally or in analog form have been proposed in [5], [7]- [9], [13], [17], and [19] to adapt SCL and ECL coefficients. In [5], [9], and [19] there are variations in the architecture of feedforward implementation.…”
Section: A Need For Adaptationmentioning
confidence: 99%
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“…In the first approach, the amplifier is operated at a point further in the linear region, or equivalently, a point with a large power input back-off (IBO). These complex gains are used to compensate for drifts in the main and error amplifier gains [23][24][25][26][27]. The second approach is to use a linearization technique such as predistortion, feed-forward (FF), feedback, and envelope elimination and restoration approaches [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%