Behavioral Modelling and Predistortion of Wideband Wireless by Fadhel M. Ghannouchi, Oualid Hammi, Mohamed Helaoui

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By Fadhel M. Ghannouchi, Oualid Hammi, Mohamed Helaoui

Covers theoretical and useful features regarding the behavioral modelling and predistortion of instant transmitters and gear amplifiers. It contains simulation software program that allows the clients to use the speculation offered within the e-book. within the first part, the reader is given the overall history of nonlinear dynamic structures besides their behavioral modelling from all its features. within the moment half, a complete compilation of behavioral versions formulations and buildings is equipped together with reminiscence polynomial dependent versions, field orientated types similar to Hammerstein-based and Wiener-based types, and neural networks-based versions. The e-book may be a helpful source for layout engineers, business engineers, functions engineers, postgraduate scholars, and researchers engaged on energy amplifiers modelling, linearization, and layout.

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The 1 dB compression point concept can be extended to the X-dB compression point. The X-dB compression point is defined in a way similar to that of the 1-dB compression point but for a gain compression of X-dB rather than 1 dB. Thus, the 3-dB compression point is the point of the Pout vs. Pin characteristic for which the actual output power of the amplifier is 3 dB less than what it would have been if the amplifier was linear; it is also the point of the AM/AM characteristic for which the gain of the device is 3 dB lower than its small signal value.

In this figure, the ideal DPD refers to a hypothetical DPD system that will generate an output signal, yDPD_ideal (n), when its input signal is xDPD (n). 3b. In this case, the linearized DUT system is made of the DPD model and the actual DUT. Thus, the signal yLDUT_meas (n) corresponds to the measured waveform at the output of the DUT when the DPD model is applied. The signal yLDUT_ideal (n) represents the signal that should ideally be obtained at the output of the linearized DUT when its input signal is xDPD (n).

Then, a variety of performance quantification metrics that have been reported in the literature for power amplifier (PA) behavioral models and digital predistorters will be thoroughly described. These are mainly categorized into two classes: time domain metrics and frequency domain metrics. Finally, the impact of memory effects on the performance assessment metrics is discussed and static nonlinearity cancelation techniques are introduced along with their relevance to behavior models and predistorter performance evaluation.

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