 - Digital signal processing (DSP) refersto various techniques for improving the accuracy and reliabilityof digital communications. The theory behind DSP is quite complex.Basically, DSP works by clarifying, or standardizing, the levelsor states of a digital signal. ADSP circuit is able to differentiate between human-made signals,which are orderly, and noise, which is inherentlychaotic.All communications circuits contain some noise.This is true whether the signals are analog or digital,and regardless of the type of information conveyed. Noise is theeternal bane of communications engineers, who are always strivingto find new ways to improve the signal-to-noise ratioin communications systems. Traditional methods of optimizing S/Nratio include increasing the transmitted signal power andincreasing the receiver sensitivity. (In wireless systems,specialized antenna systems can also help.) Digital signalprocessing dramatically improves the sensitivity of a receivingunit. The effect is most noticeable when noise competes with adesired signal. A good DSP circuit can sometimes seem like anelectronic miracle worker. But there are limits to what it cando. If the noise is so strong that all traces of the signal areobliterated, a DSP circuit cannot find any order in the chaos,and no signal will be received. If an incoming signal is analog, for example astandard television broadcast station, the signal is firstconverted to digital form by an analog-to-digital converter(ADC). The resulting digital signal has two or more levels.Ideally, these levels are always predictable, exact voltages orcurrents. However, because the incoming signal contains noise,the levels are not always at the standard values. The DSP circuitadjusts the levels so they are at the correct values. Thispractically eliminates the noise. The digital signal is thenconverted back to analog from via a digital-to-analogconverter (DAC). If a received signal is digital, for examplecomputer data, then the ADC and DAC are not necessary. The DSPacts directly on the incoming signal, eliminating irregularitiescaused by noise, and thereby minimizing the number of errors perunit time.
| CONTRIBUTORS: |
David Brancato, Mark Denni, and Vincent Martinez |
| LAST UPDATED: |
11 Aug 2002
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