Intersymbol interference
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In telecommunication, intersymbol interference (ISI) is a form of distortion of a signal in which one symbol interferes with subsequent symbols. This is an unwanted phenomenon as the previous symbols have similar effect as noise, thus making the communication less reliable. ISI is usually caused by multipath propagation and the inherent non-linear frequency response of a channel. Ways to fight against intersymbol interference include adaptive equalization and error correcting codes.
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[edit] Causes
[edit] Multipath propagation
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For more details on multipath propagation, see multipath.
One of the causes of intersymbol interference is what is known as multipath propagation in which a wireless signal from a transmitter reaches the receiver via many different paths. The causes of this include reflection (for instance, the signal may bounce off buildings), refraction (such as through the foliage of a tree) and atmospheric effects such as atmospheric ducting and ionospheric reflection. Since all of these paths are different lengths - plus some of these effects will also slow the signal down - this results in the different versions of the signal arriving at different times. This delay means that part or all of a given symbol will be spread into the subsequent symbols, thereby interfering with the correct detection of those symbols. Additionally, the various paths often distort the amplitude and/or phase of the signal thereby causing further interference with the received signal.
[edit] Bandlimited channels
Another cause of intersymbol interference is the transmission of a signal through a bandlimited channel, i.e., one where the frequency response is zero above a certain frequency (the cutoff frequency). Passing a signal through such a channel results in the removal of frequency components above this cutoff frequency; in addition, the amplitude of the frequency components below the cutoff frequency may also be attenuated by the channel.
This filtering of the transmitted signal affects the shape of the pulse that arrives at the receiver. The first image to the left demonstrates this by showing the effects of filtering a rectangular pulse; not only is the shape of the pulse within the first symbol period changed, but it is spread out over the subsequent symbol periods. When a message is transmitted through such a channel, the spread pulse of each individual symbol will interfere with following symbols.
As opposed to multipath propagation, bandlimited channels are present in both wired and wireless communications. The limitation is often imposed by the desire to operate multiple independent signals through the same area/cable; due to this, each system is typically allocated a piece of the total bandwidth available. For wireless systems, they may be allocated a slice of the electromagnetic spectrum to transmit in (for example, FM radio is often broadcast in the 87.5MHz - 108MHz range). This allocation is usually administered by a government agency; in the case of the United States this is the FCC. In a wired system, such as an optical fiber cable, the allocation will be decided by the owner of the cable.
The bandlimiting can also be due to the physical properties of the medium - for instance, the cable being used in a wired system may have a cutoff frequency above which practically none of the transmitted signal will propagate.
Communication systems that transmit data over bandlimited channels usually implement pulse shaping to avoid interference caused by the bandwidth limitation. If the channel frequency response is flat and the shaping filter has a finite bandwidh, it is possible to communicate with no ISI at all. Often the channel response is not known beforehand, and an adaptive equalizer is used to compensate the frequency response.
[edit] Effects on eye patterns
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For more details on eye patterns, see eye pattern.
An eye pattern, which overlays many samples of a signal, can give a graphical representation of the signal characteristics. The first image below is the eye pattern for a binary phase-shift keying (PSK) system in which a one is represented by an amplitude of -1 and a zero by an amplitude of +1. The current sampling time is at the center of the image and the previous and next sampling times are at the edges of the image. The various transitions from one sampling time to another (such as one-to-zero, one-to-one and so forth) can clearly be seen on the diagram.
The noise margin - the amount of noise required to cause the receiver to get an error - is given by the distance between the signal and the zero amplitude point at the sampling time; in other words, the further from zero at the sampling time the signal is the better. For the signal to be correctly interpreted, it must be sampled somewhere between the two points where the zero-to-one and one-to-zero transitions cross. Again, the further apart these points are the better, as this means the signal will be less sensitive to errors in the timing of the samples at the receiver.
The effects of ISI are shown in the second image which is an eye pattern of the same system when operating over a multipath channel. The effects of receiving delayed and distorted versions of the signal can be seen in the loss of definition of the signal transitions. It also reduces both the noise margin and the window in which the signal can be sampled, which shows that the performance of the system will be worse (i.e. it will have a greater bit error ratio).
 The eye diagram of a binary PSK system |
 The eye diagram of the same system with multipath effects added |
[edit] Countering ISI
There are several techniques in telecommunication and data storage that try to work around the problem of intersymbol interference.
- Design systems such that the impulse response is short enough that very little energy from one symbol smears into the next symbol.
- Accept the fact that the overall impulse response oscillates up and down for several symbol times. Design the system so that at the precise point where the receiver samples the current symbol, the impulse response of all previous symbols is exactly crossing zero at that point -- in other words, use a filter satisfying the Nyquist ISI criterion, so it has the zero-ISI property at the sample points. See Nyquist ISI criterion for details.
- Deliberately spread out the impulse response of a single symbol so that it is non-zero over several sampling times. Even though it's impossible to tell the difference between a "1" bit and a "0" bit if the receiver only looks at one sample, the receiver can take a series of samples and figure out which binary sequence, when spread out by the (well-characterized) impulse response, most closely matches the observed series of samples (partial response maximum likelihood PRML). With an appropriate convolutional code (trellis modulation) on the transmitter and the Viterbi algorithm at the receiver, this can correct for impulse noise that destroys any one sample, because the effect of one bit will be evident in several samples.
- 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, hard drive manufacturers found they could pack much more data on a disk platter when they switched from Modified Frequency Modulation 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.
