Baseband communication is the simplest form of analog communication.
Channel coding's error correction capability compensates for the increased error probability due to the necessitated reduced bit energy if the signal-to-noise ration is large enough.
Shannon derived the maximum datarate of a source coder's output that can be transmitted through a bandlimited additive white noise channel with no error.
Both wireline and wireless channels share characteristics, allowing us to use a common model for how the channel affects transmitted signals.
Several properties of digital communication systems make them preferable to analog systems.
Several properties of digital communication systems make them preferable to analog systems.
So-called linear codes create error-correction bits by combining the data bits linearly. Topics discussed include generator matrices and the Hamming distance.
Examples with the use of matched filters.
Analog-to-digital converters introduce quantization noise due to their finite wordlength. The signal-to-noise ratio (SNR) increases by 6 dB per bit.
In this module, we will use the 56002 to measure noise introduced by quantization and compare the performance of linear and logarithmic quantization. First, we will write a program to perform N-bit (N less than or equal to 16) linear quantization and logarithmic (mu-law) quantization. Then will use that program to compare the techniques for simple signals and audio signals.
A description of matched filters, which is a demodulation technique with LTI filters which achieves maximum SNR.
An analysis of matched filters in the frequency domain.
Increasing the bandwidth of an amplitude modulated signal increases the signal-to-noise-ratio.
