Developing smarter RF systems with model-based design

Model-based design saves time and money by moving design tasks from the lab and field to the desktop. It provides a common design environment that links designs directly to requirements, allowing you to refine algorithms through multidomain simulation, automatically generate embedded code, and develop and reuse test suites. The process increases your confidence that your initial physical prototypes and embedded code will work.
Long used in automotive and aerospace applications, model-based design is also applicable to RF systems, as described by Ken Karnofsky, a senior strategist for signal processing applications with MathWorks, in the Q&A below.

Rick Nelson: In your professional opinion, what is the most common RF system design challenge today?
Ken Karnofsky: RF system integration has become increasingly difficult, pushing the discovery of critical problems to the end of the development process when they’re most expensive to fix. Developing agile or smart RF systems takes a team of engineers possessing multiple design skills: system architecture, DSP, antenna, RF, mixed-signal, digital-hardware, and embedded-software. Most teams don’t have an expert for every area, and even if they do, each specialist uses his or her favored tool.

RN: What other challenges should design teams be mindful of when developing RF systems?
KK: RF system engineers should be aware of the impact of highly integrated RF devices on different stages of development as well as the complications that arise when different tools are used for different system components. For example, researchers can’t effectively explore 5G hybrid beamforming techniques when they use different tools for digital and RF design. Advanced technology teams can’t prove their concepts in hardware prototypes quickly enough when they rely on other teams for RTL implementation. Design teams can spend too much time debugging highly complex adaptive radio designs in the hardware lab or in the field.

RN: Are there any notable developments that can provide relief to RF system designers?
KK: These challenges have sparked the application of model-based design to RF systems, including enhanced techniques for jointly modeling and simulating RF, antenna, and digital elements. These techniques include faster simulation of complex RF architectures to facilitate rapid design exploration. They also deliver connectivity to a range of SDR and RF test hardware to accelerate and lower the cost of prototyping, design verification, and field trials of advanced technologies.

RN: What capabilities are made accessible with this modeling and simulation software?
KK: System engineers can quickly build reference designs and use algorithm-to-antenna simulation to provide insight into component interactions, exposing integration issues before building hardware and enabling more rigorous system verification much earlier in the development process. Simulations also can eliminate many design, configuration, and integration errors before building hardware. Design teams can use software like MATLAB and Simulink to integrate highly accurate RF and antenna modeling with advanced DSP algorithm design and implementation. This enables more effective collaboration among RF, digital, and system engineers to simulate faster development cycles and more thorough design verification.

RN: Beyond modeling and simulation software, how does model-based design specifically optimize the development process?
KK: Model-based design allows engineers to automatically generate HDL and C code from the models for hardware and software implementation of algorithms and control logic. As a result, algorithm designers can quickly develop hardware prototypes and create production-quality IP implementations. The algorithm-to-antenna models provide a reusable test bench throughout the development process, saving time and ensuring consistency of testing. These combined capabilities enable faster design iterations and streamline verification. In fact, an upfront investment in modeling and code generation has been shown to reduce overall development time by 30% or more.

RN: Looking toward emerging technologies like 5G, what does the future hold for RF system design?
KK: Emerging technologies will only deepen the need for highly integrated design environments and flexible connectivity to prototyping and test hardware. Technologies being developed for 5G such as massive MIMO, mmWave, and new modulation schemes will require innovative combinations of new baseband technologies and RF architectures, and IoT devices will require power-efficient RF modules to add wireless connectivity.