Abstract
Feedforward linearization has advantages in bandwidth and generality over other linearization methods. However, it is based on the subtraction of nearly equal quantities, so its major parameters must adapt to changes in environmental or operating conditions. This paper is the first published analysis of adaptation behavior in feedforward amplifier linearizers. As such, it presents an analytical framework and several new results, including convergence time and coefficient jitter, a bias effect that leads to extreme accuracy requirements in one coefficient, the effect of delay mismatch, and the mitigating effects of a filter inserted in one adaptation path.
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