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Low-noise amplifier design and optimization
2008 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Low-Noise Amplifiers are key components in the receiving end of nearly every communications system. The wanted input signal of these systems is usually very weak and the primary purpose of the LNA is consequently to amplify the signal while at the same time adding as little additional noise as possible. Its performance is measured in a number of figures of merit among which gain and noise figure are most notable while dynamic range, return loss and stability are examples of others. In May 2005 a four year design study entitled EISCAT_3D was initialized. Its purpose was to investigate the feasibility of a next-generation incoherent scatter radar system. One of the responsibilities of EISLAB at LuleƄ University of Technology is to design a receiver front-end, which include an LNA with extremely high performance requirements. For that reason a MATLAB Particle Swarm Optimization implementation was developed to iteratively find a solution to optimal component values for a user definable LNA topology. In this master's thesis, the radio frequency concepts essential to traditional LNA design as well as the design procedure itself are explained. A description to the optimizer is then given, including a chapter on 2-port noise calculations. With the objective to find an LNA design with even higher performance than the previously designed EISCAT_3D LNA, four topologies are evaluated using the optimizer while consistently targeting the EISCAT_3D specifications. These topologies include the original reference design and one that employs the inductive source degeneration design technique. The latter showed significantly improved performance with an approximate 2 dB gain increase and 0.1 dB noise figure reduction while still maintaining the return loss and stability requirements.

Place, publisher, year, edition, pages
Keyword [en]
Technology, LNA, Low-Noise Amplifier, PSO, Particle Swarm Optimization, EISCAT
Keyword [sv]
URN: urn:nbn:se:ltu:diva-59123ISRN: LTU-EX--08/230--SELocal ID: fa645ea8-4674-456c-a847-b9083088861eOAI: diva2:1032511
Subject / course
Student thesis, at least 30 credits
Educational program
Electrical Engineering, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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