JPL's Wireless Communication Reference Website Chapter: Analog and Digital Transmission

Noise

The performance of wireless communication systems is highly determined by noise. Particularly if signals are in a fade, the signal-to-noise ratio can be low and bursts of error can occur.

This is other argued that wireless systems, in particular cellular systems with dense frequency reuse, are interference-limited rather than noise-limited. However, any (digital) signal processing algorithm that attempts to remove, cancel or attenuate such interference increases the noise. The ability to separate multiple interfering signals is critically determined by the signal-to-noise ratio.

Additive White Gaussian Noise (AWGN)

A basic and generally accepted model for thermal noise in communication channels, is the set of assumptions that

• the noise is additive, i.e., the received signal equals the transmit signal plus some noise, where the noise is statistically independent of the signal.
• the noise is white, i.e, the power spectral density is flat, so the auto correlation of the noise in time domain is zero for any non-zero time offset.
• the noise samples have a Gaussian distribution.

Mostly it is also assumed that the channel is Linear and Time Invariant (LTI), sometimes also frequency non-selective.

Exercise

Which of the above assumptions are realistic in a wireless channel?

Typical causes why the noise factor n is larger than unity are

• Receiver noise
• Man made or industrial noise

At 900 MHz, the man made noise power level can easily be 20 dB (100 times) above the thermal level.

Exercise

Show that the ratio E_b/N₀ is a dimension-free unit.

Further reading

		The matched filter principle for signals transmitted over LTI AWGN channels

• Matched Filters
• Link Budget
• man made noise: pdf file
• Techniques to mitigate the effect of noise:
  • Diversity reception

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