Abstract:
In a typical communication system, the source originates the message such as a human
voice, a teletype message or data and it passes through the channel. A channel acts partly
as a filter to attenuate and distort the signal and as result the data symbols are smeared
into each other. This spreading and smearing of symbols causes the energy from one
symbol to effect the next one in such a way that the received signal has a higher
probability of being interpreted incorrectly. This is called as Inter Symbol Interference or
ISI. The main problem is that energy, which we wish to confine to one symbol, leaks into
others. An Equalizer is a compensator for channel distortion i.e. it can prevent this energy
leakage into another symbol or symbols. If the channel is time varying an adaptive
equalizer is used to counter the effect of the ISI introduced by the channel. Each adaptive
equalizer is based on a particular algorithm or principle, which provides the cost function.
The requirement is to design an equalizer filter in such a way that it minimizes the cost
function. The purpose of this term paper is to compare different adaptive equalization
techniques and their convergence rates and their implementation on a TMS320C6711
DSP processor.
