Mixed-Signal Analysis

At the highest level of abstraction, you can use MATLAB to analyze basic system architectures; for example, which is better: a second or third order sigma-delta modulator? What type of PLL is best? What do the Bode plots say about system stability?

Use analysis tools in MATLAB and Simulink to explore the design space and find the best starting point for your design. For example, Mixed-Signal Blockset uses MATLAB functionality to perform closed- and open-loop static analysis of PLLs and rapidly design loop filters.

MATLAB provides greater analysis and visualization functionality than spreadsheets or traditional programming languages like C/C++. However, you don’t have to abandon your existing investments; MATLAB works with Microsoft^® Excel^® and with C/C++.

Mixed-Signal Verification

System-level models must be linked to the next stages in the design flow. You have different ways to use your MATLAB and Simulink models as test harnesses for SPICE models, HDL code, or hardware.

Cosimulation is a run-time link between different tools; at every simulation time step, data is exchanged between tools, enabling them to run together to simulate a model. In the analog domain, Cadence^® Spectre^® AMS Designer provides cosimulation links to Simulink. In the digital domain, HDL Verifier™ provides links to third-party HDL simulators and development boards for FPGA-in-the-loop testing.

For regression testing and reuse in functional verification environments, you can export MATLAB algorithms and Simulink models as SystemVerilog modules taking advantage of the DPI-C interface.

You can analyze IC simulation results with MATLAB to visualize data more effectively and to further refine behavioral models using optimization, machine learning, or deep learning techniques.

The final level of mixed-signal verification is device testing. At this stage, MATLAB and Simulink integrate with a variety of test equipment, enabling you to build test systems that create test vectors via models, control test equipment, and analyze the results.

Data Converters (ADC/DAC)

The ability to rapidly simulate continuous- and discrete-time signals is key to the design and verification of analog-to-digital converters (ADCs). Because Simulink allows modeling in the same environment analog and digital hardware, you can design an ADC in a fraction of the time required by SPICE tools.

Doing rapid ADC design with Simulink enables faster parameter sweeps, allowing engineers to perform detailed verification in less time. Using Mixed-Signal Blockset testbenches, you can rapidly assess integral and differential nonlinearity and noise performance.

Digital Predistortion (DPD) of RF Power Amplifiers

Digital predistortion is simple in theory, but difficult in practice. MATLAB provides a unifying environment for controlling test equipment, analyzing complex data, and building algorithms for DSPs or FPGAs while having an in-depth understanding of the effects introduced by RF power amplifiers (PA).

In MATLAB, you can easily build a PA model based on modified Volterra series, including memory and non-linearity, and simulate it using RF Blockset™ Circuit Envelope. Simulating the RF PA in closed loop with your own DPD algorithm allows you to estimate timing, quantization, and additional RF effects before going to the lab.