Behavioral Modeling of Radio Frequency Transmitters

The dependence of modern wireless communication systems on the fidelity ofthe transmitter has increased the importance of modeling these components.Behavioral modeling is a commonly used technique to find the input-outputrelationship of a system, without the need for the knowledge of the specificcomponents. There have been many models proposed in the literature, whichhas made it difficult to choose models suitable for the application at hand. Byanalyzing and categorizing these models depending on the type of distortionsthey can describe, it becomes possible to understand their distortion handlingcapabilities. Such an analysis led to the design of two new behavioral models,one customized for power amplifiers and the other for modulators.Once different models are analyzed, their usefulness is determined in anexperimental setup. Different models have different modeling capabilities.While some may be able to model any nonlinear function with high accuracy,others may be capable of modeling at low computational cost. Theaccuracy/complexity tradeoff for some commonly-used behavioral models isanalyzed in this thesis.In Paper [A], a new behavioral model is proposed for power amplifiersthat combines two commonly used modeling techniques. The performance ofthis model is shown to be better than the two models it is based on, and issuesin identification are also discussed.In Paper [B], a new dual-input model is constructed for modulators. Thismodel has the ability to describe nonlinear imbalance in a modulator. Differentvariants of this model are also proposed, to reduce the computationalcomplexity.In Paper [C], a detailed analysis on the accuracy/complexity tradeoff forsome commonly-used power amplifier behavioral models is presented. Afterfinding the computational complexity in floating point operations per sample,an experimental setup is used to show that among models studied, the generalizedmemory polynomial model has the best accuracy/complexity tradeoff