RF Blockset™ (formerly SimRF™) extends Simulink® with blocks for designing RF systems and simulating their performance, taking into account the effects of impedance mismatches, wideband spectral regrowth, and interfering and blocking signals together with standard signals, digital signal processing algorithms, and control logic.
RF Blockset enables you to model and rapidly simulate RF transmitters and receivers for wireless applications such as radar or communication systems.
You can use RF Blockset to build system-level executable specifications and perform what-if analyses with different RF front-end architectures, or you can commit to a particular architecture and use simulation to develop digital signal processing algorithms to control the performance or mitigate impairments. With RF Blockset models, you can refine the executable specifications of the RF subsystem, evaluate the performance of off-the-shelf commercial components, and improve communication between system architects and RF or analog engineers.
By integrating RF Blockset models with communications algorithms, you can model digitally-assisted systems such as RF receivers with adaptive automatic gain control (AGC) and RF transmitters with digital predistortion (DPD) architectures based on nested feedback loops..
You can improve the accuracy of your model following a bottom-up approach by importing measurement data such as Touchstone files and AM/AM AM/PM data. You can use S-parameters in RF Blockset models and estimate frequency-dependent impedance mismatches between linear and nonlinear components in the time and frequency domains.
The set of RF impairments you can model in RF Blockset includes:
You can build RF receivers and transmitters by connecting blocks from the RF Blockset component library, or you can automatically generate an RF Blockset model using the RF Budget Analyzer app. With the RF Budget Analyzer app you can graphically build, or script in MATLAB, the analysis of a cascade of RF components in terms of noise, power, gain, and third-order nonlinearity. You can also generate an RF Blockset model and test bench for multicarrier circuit envelope simulation.
The RF Budget Analyzer app lets you rapidly start modeling RF transmitters and receivers for wireless applications and validate simulation results in different operating conditions by comparing them with analytical predictions. You can use this app to determine the system-level specs of your RF transceiver instead of relying on custom spreadsheets and complex computations.
You can use the automatically generated model as a baseline for further elaboration of the RF architecture and for simulation effects of imperfections that cannot be accounted for analytically, such as leakage, interferers, and MIMO architectures.
RF Blockset provides two modeling libraries for describing RF systems at different abstraction levels. Digital signal processing engineers can use the Equivalent Baseband library to estimate the impact of RF phenomena on overall system performance. RF designers can use the Circuit Envelope library to refine transceiver architectures with increased modeling fidelity.
At a higher level of abstraction, you can model a chain of RF components using blocks from the Equivalent Baseband library. You can perform budget analysis and simulations of your system, including RF impairments such as noise and odd-order nonlinearity. When you use blocks from the Equivalent Baseband library, the simulation is performed using a baseband equivalent model of the RF chain. This enables single-carrier simulation of super heterodyne transceivers, taking into account in-band spectral regrowth, noise, and impedance mismatches among blocks.
At a lower level of abstraction, blocks from the Circuit Envelope library let you model arbitrary topologies, examine quadrature architectures for your RF system, and track the effects of RF impairments through the model. When you use blocks from the Circuit Envelope library, signals in the RF Blockset models are represented as voltages and currents. As a result, impedance mismatch, reflection, and finite isolation are correctly taken into account.
RF Blockset provides models of amplifiers, mixers, impedances, transmission lines, filters, and other RF components. For amplifiers and mixers, you can specify linear and nonlinear properties such as component gain, noise figure, second-order and third-order intercept points (IP2 and IP3), 1 dB compression point, and saturation power.
With components such as power combiners, splitters, circulators, and transformers you can build arbitrary RF networks based on data sheet parameters and define the system specifications following a top-down approach. Frequency-dependent components enable you to evaluate the effects of impedance mismatch, reflection, finite-isolation, and leakage.
With tunable components such as variable gain amplifiers, attenuators, and phase shifters you can build adaptive RF systems with characteristics directly controlled by time-varying Simulink signals. This enables you to embed control logic and signal processing algorithms in the simulation of your RF front end to develop, for example, adaptive impedance tuning, gain control, hybrid beamforming, or digital predistortion.
You can describe components using S-parameters and AM/AM AM/PM data. By specifying the input and output impedance of linear and nonlinear components you can estimate the effect of frequency-dependent impedance mismatches on noise and power transfer.
You can author your own RF models using the Simscape language and build custom RF components (requires Simscape™). For example, you can model power amplifiers using the Simscape language to define custom equations based on modified Volterra series. With Simscape you can model low-frequency analog electronics chains and simulate them with RF Blockset.