cpfsk matlab,Communications Toolbox

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Communications Toolbox

Design and simulate the physical layer of communications

systems

Communications Toolbox™ provides algorithms and apps for the analysis, design, end-to-end

simulation, and verification of communications systems. Toolbox algorithms including

channel coding, modulation, MIMO, and OFDM enable you to compose and simulate a

physical layer model of your standard-based or custom-designed wireless

communications system.

The toolbox provides a waveform generator app, constellation and eye diagrams,

bit-error-rate, and other analysis tools and scopes for validating your designs.

These tools enable you to generate and analyze signals, visualize channel

characteristics, and obtain performance metrics such as error vector magnitude

(EVM). The toolbox includes SISO and MIMO statistical and spatial channel models.

Channel profile options include Rayleigh, Rician, and WINNER II models. It also

includes RF impairments, including RF nonlinearity and carrier offset and

compensation algorithms, including carrier and symbol timing synchronizers. These

algorithms enable you to realistically model link-level specifications and

compensate for the effects of channel degradations.

Using Communications Toolbox with RF instruments or hardware support packages, you can connect your

transmitter and receiver models to radio devices and verify your designs with

over-the-air testing.

Learn the basics of Communications Toolbox

Physical layer features including waveform generation, source coding, error control

coding, modulation, MIMO, space-time coding, filtering, equalization, and

synchronization

Behavioral RF radio modeling and impairment correction

Site and terrain visualization, propagation model specification (including Longley-Rice),

signal strength, signal coverage maps, and static and fading channel models

Link-level communications systems simulation and analysis examples

DLL, MAC sublayer, and LLC sublayer examples

System models compliant with various standards

Waveform generation, visualization, and performance analysis

Use deep learning in wireless communications systems

Generate standalone applications for desktop computers and embedded targets

Support for third-party software-defined radio hardware, such as Xilinx®, RTL-SDR, ADALM-PLUTO, and USRP™ radios