Modern RF systems consist of high-frequency analog electronics (the front end) and adaptive digital algorithms.

One of the primary challenges in RF system design is reducing the overall area, power, and cost for RF front ends—generally wireless transmitters and transceivers. For this reason, smart RF system design relies heavily on compensating DSP algorithms, adaptive filtering, and control logic to optimize these performance factors and to calibrate and compensate for RF impairments.

Algorithms such as digital pre-distortion (DPD), automatic gain control (AGC), beamforming, and adaptive filtering are an integral part of today’s communications and radar systems. RF system algorithms, such as the ones required by emerging 5G systems, need to be designed together with models of the antenna front end, analog/mixed-signal components, and the communication channel. Rapid system-level simulation is an essential requirement to efficiently explore design tradeoffs.

MATLAB^® and Simulink^® provide the required tools for supporting all the RF system design tasks, from system analysis to algorithm development and lab prototyping. Modeling and simulating RF, analog, and digital systems together enables faster development and easier debugging. The simulation speed achieved with circuit envelope simulation is the key enabler to managing the complexity of today’s wireless systems.

Learn more about related topics:

• Generating standard signals for LTE, WLAN, and 5G communications systems
• Developing beamforming algorithms and designing antenna arrays
• Understanding massive MIMO communications systems
• Using MIMO fading channel models and channel equalization algorithms
• Designing and simulating analog/mixed-signal components
• Performing rapid prototyping using commercial SDR platforms
• Using MATLAB for wireless communications system design