Binary data modulation with coding

When we design a communication system, we need to consider transmitter and receiver structures, probability of error, bandwidth occupancy of the modulated signal and bandwidth efficiency. Communication performance is critical factor in achieving error free transmission.


Let’s discuss the main blocks in a communication system and the way to organize them to achieve higher performance. Data to be sent is generated in the data source and fed in to the channel encoder. The purpose of the channel encoder is introducing redundancy bits to combat the effects of noise and interference over the channel. Channel coding is referred as a signal transformation designed to improve communication performance. Convolution coding is a type of channel coding. The importance characteristic of convolution coding is that coder has memory. K is a parameter called constraint length in the convolution coder. The output n-tuple emitted by coder is not only a function of input k-tuple, but also it is a function of the previous K-1 input k-tuple. 


The output of the channel encoder fed in to the digital modulator. The primary purpose of the digital modulator is to map the binary information sequence into signals suitable for transmission over the channel. We have to test Coherent phase shift keying (PSK) and Coherent frequency shift keying (FSK) modulation techniques in our communication system. Coherent receiver means receiver has a phase recovery circuitry. Receiver knows both the frequency and the phase of the carrier signal used in the transmission. PSK means signals carries information in the phase, and FSK means signal carries information in the frequency.


Modulated signal is transmitted via communication channel. Communication channel is the physical channel we use to transmit data for transmitter to the receiver. The essential feature in this physical medium is the transmitted signals are corrupted in a random manner due to various mechanisms. Here we have used Additive White Gaussian Noise channel for our simulations. Modulated signal transmitted over the channel and then converted back to sequence of binary data in the demodulator. Chanel decoder attempts to decode the channel encoded sequence. As the channel decoder in the receiver we can use maximum likelihood decoding and Viterbi decoding. We used Viterbi decoding for our simulations. The signal at the channel decoder in our scenario is the approximation of the original data.


We need to consider probability of error, bandwidth occupancy of the modulated signal and bandwidth efficiency of the communication system in designing. With coding we can achieve lower probability of error without increasing the signal to noise ratio. By introducing channel coding to the modulation, we raised the performance of the communication system. But when we used coding we need higher bandwidth for data transmission. Bandwidth the price we have to pay for the higher performance with channel coding.


We can achieve lower bit error probability in using BPSK modulation over BFSK modulation. BPSK showed higher performance than BFSK for same signal to noise ratio.With coding we can increase the performance of the communication system. When we use channel coding we can achieve the same probability of error level that we have in modulation with lower signal to noise ratio. We saw that code rate ½ perform well over code rate 1/3 at lower probability of error levels. But there is a price that we have to pay when we use channel coding in communication systems. When we use channel coding we need higher bandwidth, because we transmit more bits in the same bit duration. So higher code rates will result higher spectral occupancy. Normally, BPSK has less spectral occupancy than BFSK. 


BPSK is the best modulation technique for binary data transmission. BPSK with channel coding raised the performance level of the communication system, resulting higher utilization of the bandwidth.