Skip to content

Latest commit

 

History

History
74 lines (49 loc) · 2.8 KB

README.md

File metadata and controls

74 lines (49 loc) · 2.8 KB
Raw

A communication system simulation

This program simulates a basic communication system using Matlab, and it plots BER curves in order to compare the performance of several codification algorithms. It includes the following components:

Diagram

main.m is the main file.

Components and options

Input voices

Voz.wav is the audio file that contains the message. The program plots the input signal.

Output

fundamental_frequency: the fundamental frequency of the message in the audio file.

x: vector that contains the message.

Quantization

This module plots the first input signal with the levels of quantization and the quantized signal.

Options

level: the number of levels for quantization.

option_quantization: quantization processes. Available options:

  • 1 - Uniform
  • 2 - Mu-Law
  • 4 - A-Law

Output

xq: quantized message.

Output

quantization_error: quantization error.

Codification

This simulation codifies the message using the following methods:

  • Hamming (7,4)
  • Convolutional codes: soft decision
  • Convolutional codes: hard decision

Modulation

This module modulates the message according the codification, and it plots the constellation for the selected modulation.

Options

option_modulation: modulation processes. Available options:

  • 1 - BPSK
  • 2 - QPSK
  • 3 - BPSK and QPSK

Output

Message modulated according to the selected modulation:

BPSK variables: bitsm1 (no codification), bitsm2 (Hamming), bitsm3 (Convolutionl)

QPSK variables: bitsmqpsk1 (no codification), bitsmqpsk2 (Hamming), bitsmqpsk3 (Convolutional)

BER Curves

This module uses a loop in order to simulate an AWGN channel with several Eb/N0 values. Eb/N0 is the energy per bit to noise power spectral density ratio. Value between 1 and 6, where 6 is for the least noisy channel.

Demodulation and decodification are performed in this loop. The program plots the BER curves of several codification algorithms.

Output

Probability of error gives the average rate of occurrence of decoding errors. Pe error for the codification algorithms according to the selected modulation:

BPSK variables: errorpe_bpsk_nocod (no codification), errorpe_bpsk_hamming (Hamming), errorpe_bpsk_hard (Convolutionl: Hard decision), errorpe_bpsk_soft (Convolutional: Soft decision)

QPSK variables: errorpe_qpsk_nocod (no codification), errorpe_qpsk_hamming (Hamming), errorpe_qpsk_hard (Convolutional: Hard decision)

Graphs

Plots

Acknowledgements

This program was developed during the communication course "Comunicación y codificación digital" at Universidad de las Fuerzas Armadas ESPE.