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Turning MBSE Inside-Out For An RF EDA Shift Left

Bring RF system engineering efforts into the virtual space with high-fidelity behavioral models.

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Model-based systems engineering (MBSE) focuses on creating and exploiting domain models in a digital modeling language. RF system designers trying to use generic MBSE tools soon run into a problem: developing behavioral models. Without high-fidelity models, simulations miss real-world results, and a digital twin won’t be worth the effort. What’s helping RF teams get engineering tasks done in virtual space with less time, cost, and risk? Here’s a quick look at turning MBSE inside-out for an RF EDA shift left.

Requirements traceability isn’t the only goal

MBSE workflows are usually serial. They start with requirements, then move to structure, then behavior, and then verification and validation. This flow delivers outstanding requirements traceability. But, for an MBSE effort to succeed, simulations must match measurements.

Complexity changes everything. Creating high-fidelity behavioral models, with the right parameters, requires domain knowledge and time. Real-world effects are difficult to represent accurately in generic modeling tools. Simulations open an accuracy gap. The mismatch to physical results erodes trust in the virtual environment.

Fig. 1: An accuracy gap shows up when behavioral models lack fidelity.

Closing the gap with proven behavioral models

Still, engineering RF systems in virtual space is appealing. It’s difficult and prohibitively expensive, if not impossible, to physically recreate everything a system might see in the real world. There are also these factors to consider:

  • Requirements often arrive in the form of comprehensive industry specifications
  • Scenarios are crucial, defining kinematic and interference effects on a system
  • Behavioral models are complex, but definable using RF physics detail
  • Parameters go hand-in-hand with observability and measurement science

Using MBSE for RF system architecture has big implications. MBSE holds the key to earlier and more accurate system capability prediction – if the models are right. Reducing complexity through abstraction kills accuracy. Instead, complexity should be packaged in easier-to-use models in architectural frameworks.

Fig. 2: Digital modeling provides earlier confidence in system performance. (Source: Dr. Ray Kolonay, Air Force Research Laboratory)

An RF EDA tool should surround high-fidelity RF models with an easy-to-use system simulation workflow. This empowers system architects who may not be experts in RF characteristics but do understand how RF processing blocks fit together.

Digital twins should start good, get better

Shift left and “single source of truth” are parts of the MBSE value proposition. A digital twin extends MBSE to fully represent a virtual instance, sitting on three pillars:

  • A virtual prototype built around high-fidelity models in a functional framework.
  • Simulations providing stimuli and observability matching real-world conditions.
  • Updates to models and simulations based on feedback from measurements.

Keysight’s PathWave System Design brings RF-aware multi-domain modeling and simulation to system architects, designers, and verification engineers. Keysight measurement science inside provides modulated signal capability. PathWave System Design also integrates with other popular MBSE tools for mission and scenario planning, requirements management, and high-level system modeling.

Thinking about bringing RF system engineering efforts into virtual space? Keysight experts will be on a webinar broadcast live on April 26th discussing MBSE and digital twin concepts. There’s also a Keysight solution brief with more details on these ideas and how PathWave System Design fits in RF system design workflows.



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