Characteristics of RF MEMS Switches for Communication Systems

The increased growth of the applications of RF MEMS switches in modern communication systems has created an increased need for their accurate and efficient models. Artificial neural networks have appeared as a fast and efficient modelling tool providing similar accuracy as standard commercial simulation packages. This paper gives an overview of the applications of artificial neural networks in modelling of RF MEMS switches, in particular of the capacitive shunt switches, proposed by the authors of the paper. Models for the most important switch characteristics in electrical and mechanical domains are considered, as well as the inverse models aimed to determine the switch bridge dimensions for specified requirements for the switch characteristics.

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RF MEMS Switch Fabrication and Packaging

10.5772/intechopen.95003 ◽

2020 ◽

Author(s):

Lakshmi Swaminathan

Keyword(s):

Communication Systems ◽

High Performance ◽

Satellite Communication ◽

Rf Mems ◽

Mems Devices ◽

Micro Electro Mechanical Systems ◽

Mems Switches ◽

Mems Switch ◽

Hermetic Sealing ◽

Rf Mems Switches

RF (Radio Frequency) MEMS (Micro Electro Mechanical Systems) technology is the application of micromachined mechanical structures, controlled by electrical signals and interacting with signals in the RF range. The applications of these devices range from switching networks for satellite communication systems to high performance resonators and tuners. RF MEMS switches are the first and foremost MEMS devices designed for RF technology. A specialized method for fabricating microsturctures called surface micromachining process is used for fabricating the RF MEMS switches. Die level packaging using available surface mount style RF packages. The packaging process involved the design of RF feed throughs on the Alumina substrates to the die attachment, wire bonding and hermetic sealing using low temperature processes.

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Hybrid neural lumped element approach in inverse modeling of RF MEMS switches

Facta universitatis - series Electronics and Energetics ◽

10.2298/fuee2001027c ◽

2020 ◽

Vol 33 (1) ◽

pp. 27-36

Author(s):

Tomislav Ciric ◽

Zlatica Marinkovic ◽

Rohan Dhuri ◽

Olivera Pronic-Rancic ◽

Vera Markovic

Keyword(s):

Resonant Frequency ◽

Inverse Modeling ◽

Communication Systems ◽

Rf Mems ◽

Element Model ◽

Mems Switches ◽

Lumped Element ◽

Rf Mems Switches ◽

Element Approach ◽

Lumped Element Model

RF MEMS switches have been efficiently exploited in various applications in communication systems. As the dimensions of the switch bridge influence the switch behaviour, during the design of a switch it is necessary to perform inverse modeling, i.e. to determine the bridge dimensions to ensure the desired switch characteristics, such as the resonant frequency. In this paper a novel inverse modeling approach based on combination of artificial neural networks and a lumped element circuit model has been considered. This approach allows determination of the bridge fingered part length for the given resonant frequency and the bridge solid part length, generating at the same time values of the elements of the switch lumped element model. Validity of the model is demonstrated by appropriate numerical examples.

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