| Communications Toolbox 3.0 Release Notes | |
This section summarizes the new features and enhancements introduced in the Communications Toolbox 3.0:
If you are upgrading from a release earlier than Release 13, then you should see New Features.
The Communications Toolbox has a graphical user interface (GUI) called BERTool that helps you analyze communication systems' bit error rate (BER) performance. To invoke the GUI, type
bertool
in the MATLAB Command Window.
For more information and examples, see BERTool: A Bit Error Rate Analysis GUI and the Bit Error Rate Analysis Tool demo. Some of the capabilities of the GUI are also available using command-line functions, described in Performance Evaluation.
The functions in the table below enable you to measure or visualize the bit error rate performance of a communication system.
| Function | Purpose |
|---|---|
| berawgn | Error probability for uncoded AWGN channels |
| bercoding | Error probability for coded AWGN channels |
| berconfint | BER and confidence interval of Monte Carlo simulation |
| berfading | Error probability for Rayleigh fading channels |
| berfit | Fit a curve to nonsmooth empirical BER data |
| bersync | Bit error rate for imperfect synchronization |
| distspec | Compute the distance spectrum of a convolutional code |
| semianalytic | Calculate bit error rate using the semianalytic technique |
For more information and examples, see Performance Evaluation in the Communications Toolbox documentation. Some of the capabilities of these functions are also available from the BERTool GUI, described in BERTool: A Bit Error Rate Analysis GUI.
The functions in the table below enable you to equalize a signal using a linear equalizer, a decision feedback equalizer, or a maximum-likelihood sequence estimation equalizer based on the Viterbi algorithm.
| Function | Purpose |
|---|---|
| cma | Construct a constant modulus algorithm (CMA) object |
| dfe | Construct a decision feedback equalizer object |
| equalize | Equalize a signal using an equalizer object |
| lineareq | Construct a linear equalizer object |
| lms | Construct a least mean square (LMS) adaptive algorithm object |
| mlseeq | Equalize a linearly modulated signal using the Viterbi algorithm |
| normlms | Construct a normalized least mean square (LMS) adaptive algorithm object |
| rls | Construct a recursive least squares (RLS) adaptive algorithm object |
| signlms | Construct a signed least mean square (LMS) adaptive algorithm object |
| varlms | Construct a variable step size least mean square (LMS) adaptive algorithm object |
For more information and examples, see Equalizers in the Communications Toolbox documentation. See also the Adaptive Equalization Simulation demo (part I and part II).
The functions in the tables below enable you to model a Rayleigh fading channel, Rician fading channel, and binary symmetric channel.
| Function | Purpose |
|---|---|
| bsc | Model a binary symmetric channel |
| filter (for channel objects) | Filter signal with channel object |
| rayleighchan | Construct a Rayleigh fading channel object |
| reset | Reset channel object |
| ricianchan | Construct a Rician fading channel object |
For more information and examples, see Channels in the Communications Toolbox documentation.
The functions in the tables below enable you to perform block interleaving and convolutional interleaving, respectively.
Block Interleaving
| Function | Purpose |
|---|---|
| algdeintrlv | Restore ordering of symbols using algebraically derived permutation table |
| algintrlv | Reorder symbols using algebraically derived permutation table |
| deintrlv | Restore ordering of symbols |
| helscandeintrlv | Restore ordering of symbols in a helical pattern |
| helscanintrlv | Reorder symbols in a helical pattern |
| intrlv | Reorder sequence of symbols |
| matdeintrlv | Restore ordering of symbols by filling a matrix by columns and emptying it by rows |
| matintrlv | Reorder symbols by filling a matrix by rows and emptying it by columns |
| randdeintrlv | Restore ordering of symbols using a random permutation |
| randintrlv | Reorder symbols using a random permutation |
Convolutional Interleaving
| Function | Purpose |
|---|---|
| convdeintrlv | Restore ordering of symbols using shift registers |
| convintrlv | Permute symbols using shift registers |
| heldeintrlv | Restore ordering of symbols permuted using helintrlv |
| helintrlv | Permute symbols using a helical array |
| muxdeintrlv | Restore ordering of symbols using specified shift registers |
| muxintrlv | Permute symbols using shift registers with specified delays |
For more information and examples, see Interleaving in the Communications Toolbox documentation.
The functions in the table below enable you to perform Huffman coding.
| Function | Purpose |
|---|---|
| huffmandeco | Huffman decoder |
| huffmandict | Generate Huffman code dictionary for a source with known probability model |
| huffmanenco | Huffman encoder |
For more information and examples, see Huffman Coding in the Source Coding chapter of the Communications Toolbox documentation.
The functions in the table below enable you to perform rectangular pulse shaping at a transmitter and matched filtering at the corresponding receiver.
| Function | Purpose |
|---|---|
| intdump | Integrate and dump |
| rectpulse | Rectangular pulse shaping |
These functions can be useful in conjunction with the modulation functions listed below.
| | Major Bug Fixes | Utility Functions | |
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