Publication: Analysis of cartesian feedback rf power amplifier for l band frequency range using design of experiment (doe)
Loading...
Date
2008-05-01
Authors
Govindarajoo, Gunalan
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Designers of RF power amplifiers (PAs) for modern wireless systems are faced with a difficult tradeoff. On one hand, the PA consumes the lion’s share of the power budget in most transceivers. It follows that, in a cellular phone, for example, battery lifetime is largely determined by the power efficiency of the PA. On the other hand, it may be desirable to have high spectral efficiency—the ability to transmit data at the highest possible rate for a given channel bandwidth. The design conflict is that, while spectral efficiency demands a highly linear PA, power efficiency is maximized when a PA is run as a constant-envelope, nonlinear element. The current state of the art is to design a moderately linear PA and employ some linearization technique. The amplifier operates as close to saturation as possible, maximizing its power efficiency, and the linearization system maximizes the spectral efficiency in this near-saturated region. This is mainly because of the effect or influence of the sensitive elements in the design. These failures will induce a lot of money in term of reworking the rejects. For this reason, one method that is largely used to overcome this problem is by using DoE. Design of Experiment (DoE) is a structured, organized method that is used to determine the relationship between the different factors (Xs) affecting a process and the output of that process (Y). Design of Experiment involves designing a set of some desired amount of experiments, in which all relevant factors are varied systematically. When the results of these experiments are analyzed, they help to identify optimal conditions, the factors that most influence the results, and those that do not, as well as details such as the existence of interactions and synergies between factors. When applied to a well-structured matrix, analysis of variance delivers accurate results, even when the matrix that is analyzed is quite small. Today, Fisher's methods of design and analysis are international standards in business and applied science. So, this thesis is made to explain about DoE in terms of how to use it, how it can solve manufacturing problems and how important it is in the manufacturing process.