Generate signal source data and noise to simulate communication links. Visualize and analyze the performance of your communications system simulation.
|Wireless Waveform Generator||Create, impair, visualize, and export modulated waveforms|
|Uniformly distributed pseudorandom integers|
|Generate bit error patterns|
|Generate random matrix using prescribed alphabet|
|Construct combined jitter generator object|
|Construct pattern generator object|
|Generate root Zadoff-Chu sequence|
|Convert mask vector to shift for shift register configuration|
|Convert shift to mask vector for shift register configuration|
|Generate white Gaussian noise samples|
|Generate bipolar Barker code|
|Read baseband signals from file|
|Generate Gold sequence|
|Generate Hadamard code|
|Generate Kasami sequence|
|Generate OVSF code|
|Generate a pseudo-noise (PN) sequence|
|Generate RDS/RBDS waveform|
|Generate Walsh code from orthogonal set of codes|
|Barker Code Generator||Generate bipolar Barker Code|
|Baseband File Reader||Read baseband signals from file|
|Bernoulli Binary Generator||Generate Bernoulli-distributed random binary numbers|
|Gold Sequence Generator||Generate Gold sequence from set of sequences|
|Hadamard Code Generator||Generate Hadamard code from orthogonal set of codes|
|Kasami Sequence Generator||Generate Kasami sequence from set of Kasami sequences|
|OVSF Code Generator||Generate orthogonal variable spreading factor (OVSF) code from set of orthogonal codes|
|PN Sequence Generator||Generate pseudonoise sequence|
|Poisson Integer Generator||Generate Poisson-distributed random integers|
|Random Integer Generator||Generate integers randomly distributed in specified range|
|Walsh Code Generator||Generate Walsh code from orthogonal set of codes|
Create, impair, visualize, and export modulated waveforms.
Define terms related to matrices, vectors, and scalars, as well as frame-based and sample-based processing.
Error statistics and plotting.
You can generate noise for communication system modeling using the MATLAB Function block with a random number generator.
Comparison of spreading sequences for single and multiuser scenarios in single path and multipath environments.
Sending the simulation results to the MATLAB workspace and using MATLAB to analyze the data.