This paper presents a method for pruning power amplifier (PA) behavioral models and digital predistorters based on compressed sampling theory. Using this method, the number of coefficients required by behavioral models and predistorters can be significantly reduced while achieving comparable performance in terms of both modeling accuracy and suppressing distortions. Hardware measurements obtained for a Doherty PA driven by a five-carrier 100-MHz wide long-term evolution-advanced signal demonstrate the capability of the proposed method to linearize a highly nonlinear PA prototype using a minimal number of coefficients, revealing the attractive properties of the proposed method and its desirable performance. Using the proposed technique, predistorters achieving similar linearization performance while requiring significantly less coefficients than the traditional models were demonstrated.
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Abdelhafiz et al. (2014) studied this question.
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