RF Blockset enables you to model and rapidly simulate RF transmitters and receivers for wireless applications such as radar or communication systems.

You can design 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.

Use this app to determine the system-level specs of your RF transceiver instead of relying on custom spreadsheets and complex computations, and inspect results numerically or graphically by plotting different metrics.

You can also generate an RF Blockset model and test bench for multicarrier circuit envelope simulation. 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 lets you model wireless systems including adaptive RF transmitters and receivers, analog front ends, digital signal processing algorithms, and control logic.

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, analog, antenna, and RF 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.

RF Blockset provides two techniques for simulating RF systems at different abstraction levels. Digital signal processing engineers can use the Equivalent Baseband library to quickly 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 and more accurate 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 even-order and odd-order nonlinearity. You can use measurement data to characterize the nonlinear behavior and the memory of power amplifiers.

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 author your own RF models using the Simscape language and build custom RF components (requires Simscape). For example, you can define algebraic and differential equations representing arbitrary relationships between input/output voltages and currents.

With RF Blockset you can model imperfections such as:

• Even-order and odd-order nonlinearity
• Thermal noise, local oscillator phase noise, and noise with colored distribution
• Impedance mismatch, reflection, finite isolation, and leakage effects
• I/Q amplitude and phase mismatches leading to mixer images
• Phase offsets, variable group delay, and time delay
• DC conversion and DC offset

You can model amplifiers in RF Blockset using either data sheet specifications or characterization data.

For the Amplifier block, you can specify gain, noise figure or spot noise data, second-order and third-order intercept points (IP2 and IP3), 1 dB compression point, and saturation power.

You can improve the accuracy of your model following a bottom-up approach and importing measurement data. By importing Touchstone files and using S-parameters, you can model input and output impedances, gain, and reverse isolation.

For power amplifiers , you can use nonlinear characteristics such as AM/AM-AM/PM, or fit time-domain input-output narrowband or wideband characteristics using a memory polynomial, thus modeling nonlinearity and memory effects. The MATLAB fitting procedure is open and can be modified to accommodate customized workflows.

With accurate models of amplifiers, you can develop adaptive linearization algorithms such as digital predistortion (DPD), and do earlier testing of the performance of your transmitter in different operating conditions.

With RF Blockset, you can simulate at the system level the effects of noise. Passive components such as resistors, attenuators, and S-parameters generate thermal noise that is proportional to their attenuation.

For active components, you can specify the noise figure and the spot-noise data, or you can read frequency-dependent noise data from Touchstone files. You can also specify an arbitrary frequency-dependent noise distribution for local oscillators, which is particularly useful to model phase noise.

Because you can specify input and output impedances for each component, impedance mismatches affect the power transfer of the actual signal and of the noise, thus enabling the simulation and optimization of low-noise systems.

With RF Blockset Circuit Envelope library, you can import and simulate up to 8-port S-parameter data. You can build arbitrary networks by connecting S-parameters blocks to other RF components and take into account both impedance mismatches and filtering effects.

You can directly import Touchstone files, or read S-parameter data from the MATLAB workspace. The S-parameters are fitted either using a time-domain approach based on fitting a rational function on the frequency data, or using a frequency-domain approach based on the convolution of the frequency data. These two approaches let you model a wide range of different use cases, including passive and active data that introduce frequency-dependent amplitude and phase.

The noise generated by passive S-parameters is automatically included during simulation. Alternatively, for active S-parameters users can specify the frequency-dependent noise figure in Touchstone files.

The S-parameters block also lets you model data that is defined exclusively by means of amplitude characteristics. You can use S-parameters to model ideal passband filters, or to define blocks by means of high-level specifications.

With RF Blockset test benches, you can validate the performance of RF transmitters and receivers. You can use the test benches to measure the gain, noise figure, IP2, and IP3 of your system in different operating conditions. The test bench generates the required stimuli and evaluates the system response to compute the desired measurement.

The test bench blocks are useful to validate the performance of your network in the presence of imperfections that are otherwise difficult to estimate analytically. By comparing the test bench results with the expected analytical results, you gain confidence in the simulation results, you learn how to use the circuit envelope technique, and you verify that your system is correctly modeled.

The test benches can also be directly generated from the RF Budget Analyzer app and support both heterodyne as well as homodyne architectures.