OnScale Blog

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Simulation of SAW & BAW Resonators for RF Filters

  In this blog post, we'll have a look at some of the basics of electronic resonators such as: what is a resonator, the types of resonators that are most used on the market, the basic physical principles, the most important characteristics, and how to get all of that with simulation using OnScale.

How to use Simulation to Design and Optimize FBARs

In this article, we will discuss Genetic Algorithm and how it can be used for Film Bulk Acoustic Resonator (FBAR) design optimization.

What are the key performance factors for innovative RF filter design?

In today's smart devices, the RF Front-End (Also called RFFE) represents all the circuitry between High frequency data received from Antennas to near-zero frequency baseband signals.

What is an RF Front End (RFFE)?

In current mobile devices, there is a sophisticated circuitry that is responsible for converting information from the near-zero frequency baseband signals used to convey information and data to radio-signals that can be received or transmitted over the air.

How to Design a Better RF MEMS Resonator for 5G Smart Devices

In the rapidly developing world of Internet of Things (IoT), the radio frequency front-end (RFFE) of smart devices will have to handle higher data rates and access the full bandwidth of 4G/5G wireless technology. The reason for this, of course, is the growing demands of ubiquitous low latency data at higher operating frequencies required to accommodate enhanced data transmission capabilities and rapidly growing numbers of users.

How to Simulate Acoustic Filters for 5G Mobile Front-Ends

In this blog post we discuss the key solver capabilities that OnScale provides to RF engineers designing acoustic filters. We describe the process of simulating different resonators based on surface acoustic wave (SAW) and bulk acoustic wave (BAW) technology.

How to Optimize 5G SAW Filters Using OnScale

OnScale is the first CAE package to bring enterprise level simulation to the cloud. Once you upload your problem, you immediately gain access to each PC level computation and are charged on a pay-as-you-go basis. Every additional core-hour you use for your problem only costs $10 per core-hour - so our is extremely customized to your exact project needs with the goal of helping you cut costs on unnecessary license fees. In addition, our scalable HPC platform can run billion degrees of freedom problems, in parallel!  Our simulation capability along with our flexible licencing system delivered by a SaaS model allows you to accelerate R&D processes in our very secure and high performing cloud through

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