Communications Blockset

Overview of the Simulation

This example simulation starts by creating a random binary message signal. The simulation encodes the message into a convolutional code, modulates the code using the binary phase shift keying (BPSK) technique, and adds white Gaussian noise to the modulated data in order to simulate a noisy channel. Then, the simulation decodes the convolutional code while trying to correct as many noise-induced errors as possible. The decoding also involves some intermediate steps to prepare the received data for the decoding block. Finally, the simulation compares the decoded information to the original message signal in order to compute and display an error rate.

The table below indicates which blocks from the Communications Blockset appear in the model, the order they appear in the model, and the purpose each one serves.

Communications Blockset Block	Purpose in Example
Bernoulli Random Binary Generator	Create random bits to use as message.
Convolutional Encoder	Encode message using the convolutional coding technique.
BPSK Modulator Baseband	Modulate encoded message to prepare for transmission.
AWGN Channel	Transmit data, adding random numbers to simulate a noisy channel.
Sampled Quantizer Encode	Map received data to appropriate three-bit values to prepare for soft-decision decoding.
Viterbi Decoder	Decode the convolutional code using the Viterbi algorithm.
Error Rate Calculation	Compute proportion of discrepancies between original and recovered messages.

The model also uses some blocks from Simulink and the DSP Blockset:

• Unbuffer (DSP Blockset)
• Complex to Real-Imag (Simulink)
• Terminator (Simulink)
• Buffer (DSP Blockset)
• Display (Simulink)

The Example Model

Building the Model