Intersymbol interference

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In telecommunication, intersymbol interference (ISI) means a form of distortion of a signal that causes the previously transmitted symbols to have an effect on the currently received symbol. This is usually an unwanted phenomenon as the previous symbols have similar effect as noise, thus making the communication less reliable. ISI is usually caused by echoes or non-linear frequency response of the channel. Ways to fight against intersymbol interference include adaptive equalization or error correcting codes (especially soft-decoding with Viterbi algorithm).

[edit] Official definition

In telecommunication, the term intersymbol interference (ISI) has the following meanings:

1. In a digital transmission system, distortion of the received signal, which is manifested in the temporal spreading and consequent overlap of individual pulses to the degree that the receiver cannot reliably distinguish between changes of state, i.e., between individual signal elements.

At a certain threshold, intersymbol interference will compromise the integrity of the received data.

Intersymbol interference attributable to the statistical nature of quantum mechanisms sets the fundamental limit to receiver sensitivity.

Intersymbol interference may be measured by eye patterns.

2. Extraneous energy from the signal in one or more keying intervals that interferes with the reception of the signal in another keying interval.

3. The disturbance caused by extraneous energy from the signal in one or more keying intervals that interferes with the reception of the signal in another keying interval.

Source: from Federal Standard 1037C and from MIL-STD-188

[edit] Countering ISI

In ASK-like modulations it is possible to (ideally) remove the interference between different symbols using a filter satisfying the Nyquist ISI criterion: if the symbols are sent every T_B seconds and a particular filter h(t) is used so that, once sampled, it has a constant value, then the ISI is completely removed. The Nyquist ISI criterion says that, if the Fourier transform of h(t) is so that:

$\sum_{n = -\infty}^{\infty} H (f - n / T_B) = T_B$

then there will be no ISI between the different symbols and the error in the transmission can be caused only by noise.

There are several techniques in telecommunication and data storage that try to work around the problem of intersymbol interference.

In the Gaussian minimum shift keying, ISI is introduced before sending by using a gaussian filter: this way it is possible to recover lost symbols using the surrounding ones by the Viterbi algorithm.
Other techniques design symbols that are more robust against intersymbol interference. Decreasing the symbol rate (the "baud rate"), and keeping the data bit rate constant (by coding more bits per symbol), reduces intersymbol interference.
Other techniques try to compensate for intersymbol interference. For example, when hard drive manufacturers found they could pack much more data on a disk platter when they switched from MFM to Partial Response Maximum Likelihood (PRML). Even though it's impossible to tell the difference between a "1" bit and a "0" bit if you only look at the signal during that bit, you can still tell them apart by looking at a cluster of bits at once and figuring out which binary sequence, when smeared out by the (well-characterized on a particular hard drive) intersymbol interference, most closely matches the observed signal. Trellis modulation is a closely related technique.
Equalization is also frequently used to reduce the impact of intersymbol interference. See, for example, IEEE 802.3's 10GBASE-LRM Task Force, where equalization is being used to extend 10 Gigabit Ethernet's distance on 50μm multi-mode optical fiber.