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Reduction of the Envelope Fluctuations of Multi-Carrier Modulations using Adaptive Neural Fuzzy Inference Systems

In this paper, a novel scheme for reducing the envelope fluctuations in multi-carrier signals applying Adaptive Neural Fuzzy Inference Systems (ANFIS) is proposed and analyzed. Once trained with signals with very low envelope fluctuations, such as those obtained by the Active Constellation Expansion - Approximate Gradient Project (ACE-AGP) algorithm, ANFIS approximately reaches a similar reduction as with ACE-AGP for multi-carrier signals without the complexity and the large convergence time of conventional ACE-AGP. We show that our approach is less complex than other previous schemes and with better performance.