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Data Communications
Communications systems exist to transfer information from one location to another. The components of the information or message are usually known as data (derived from the Latin word 'datum' for item of information). All data are made up of unique code symbols or other entities on which the sender and receiver of the messages have agreed.
For example: binary digital data is represented by two states '0' and '1'. These are referred to as BInary digiTS or 'bits'. These bits are represented inside our computers by the voltage level of the electrical signals within storage elements; a high level could represent a '1', and a low level represent a '0'. Alternatively, the data may be represented by the presence or absence of light in an optical fiber cable.
1. Transmitter Receiver Communications Channel Source Destination
A communications process requires the following components:
• A source of the information
• A transmitter to convert the information into data signals compatible with the communications channel
• A communications channel
• A receiver to convert the data signals back into a form the destination can understand
• The destination of the information FIG. 1 shows the communications process.
FIG. 1 Communications process
Encoding is the process of converting data to code, and decoding is the process of converting code back to data. The codes that represent the data can exist in many different forms.
The transmitter encodes the information into a suitable form to be transmitted over the communications channel. The communications channel moves this signal as electro magnetic energy from the source to one or more destination receivers. The channel may convert this energy from one form to another, such as electrical to optical signals, while maintaining the integrity of the information so that the recipient can understand the message sent by the transmitter. For the communications to be successful, the source and destination must use a mutually agreed method of conveying the data. The main factors that must be considered are:
• The form of signaling and the magnitude(s) of the signals to be used
• The type of communications link (twisted pair, coaxial, optic fiber, radio etc.)
• The arrangement of signals to form character codes from which the message can be constructed
• The methods of controlling the flow of data
• The procedures for detecting and correcting errors in the transmission
The form of physical connections is defined by interface standards. Some agreed coding is applied to the message and the rules controlling the data flow and detection and correction of errors are known as protocol.
1.1. Interface standard
An interface standard defines electrical and mechanical aspects of the interface to allow the communications equipment from different manufacturers to operate together. A typical example is the EIA/TIA 232 C interface standard commonly known as RS-232-C. This specifies the following three components:
• Electrical signal characteristics
This component defines the allowable voltage levels, grounding characteristics etc.
• Mechanical characteristics
This component defines the connector arrangements and pin assignments.
• Functional description of the interchange circuits
This component defines the function of the various data, timing and control signals used at the interface.
It should be emphasized that the interface standard only defines the electrical and the mechanical aspects of the interface between devices and does not cover how data is transferred between them. Other examples of physical interfaces include EIA/TIA-485 (RS-485), X.21, G703, ISO 11801 etc.
1.2 Coding
This describes the way data is converted into symbols before transmission. The number and format of symbols used to represent each piece of data makes up the code.
Wide varieties of codes have been used for communications purposes. Early telegraph communications used Morse code with human operators as transmitter and receiver. The Baudot code introduced a constant 5-bit code length for use with mechanical telegraph transmitters and receivers. The commonly used codes for data communications today are the Extended Binary Coded Decimal Interchange Code (EBCIDIC) and the American Standard Code for Information Interchange (ASCII). The ASCII code is shown in Table 1.
Most significant bits MSB
Least significant bits LSB
Table 1 ASCII code table
1.3 protocols
A protocol is essential for defining the common message format and procedures for transferring data between all devices on the network. It includes the following important features:
• Initialization Initializes the protocol parameters and commences the data transmission.
• Framing and synchronization
Defines the start and end of the frame and how the receiver can synchronize to the data stream.
• Flow control
Ensures that the receiver is able to advise the transmitter to regulate the data flow and ensure no data is lost.
• Line control
Used with half-duplex links to reverse the roles of transmitter and receiver and begin transmission in the other direction.
• Error control
Provides techniques to check the accuracy of the received data to identify transmission errors. These include block redundancy checks and cyclic redundancy checks.
• Time out control
Procedures for transmitters to retry or abort transmission when acknowledgments are not received within agreed time limits.
Examples of some of the commonly used communications protocols are:
• Xmodem or Kermit for asynchronous file transmission
• Binary synchronous control protocol (BSC), synchronous data link control (SDLC), high level data link control (HDLC), fiber distributed data interface (FDDI), transport control protocol/Internet protocol (TCP/IP), multi-protocol label switching (MPLS) and asynchronous transfer mode (ATM) for synchronous transmissions.
Industrial protocols include manufacturing automation protocol (MAP), technical office protocol (TOP), Modbus, Data Highway Plus, HART, Fieldbus etc. Detailed discussion of protocol operation is beyond the scope of this guide.
2. Types of Communications Channels
2.1 Analog communications channels
An analog communications channel conveys analog signals, which are changing continuously in either one or a combination of frequency, phase and amplitude. These signals are commonly used for audio and video communication as illustrated in FIG. 2. It is worth noting that some fiber optic systems operate as an analog channel.
FIG. 2 Analog signals
2.2 Digital communications channels
A digital communications channel conveys digital signals, which are characterized by the use of discrete signal amplitudes. A binary digital signal, for example, has only two allowed values representing the binary digits 'ON' and 'OFF'. In fiber optic communications channels, these states are normally represented by the presence or absence of light.
Velocity of signal though channel
FIG. 3 Digital signals
3. Communications Channel Properties
The physical properties of the communications channels limit their ability to carry information in either analog or digital form. The principal effects are signal attenuation, channel bandwidth and noise.
3.1 Signal measurement on a communication channel
The majority of engineering measurements performed on voice and date systems are carried out as a measurement of power levels. The equations for power are:
P = VI
P = VR2
P = I2R
Where:
P = Power (in watts)
V = Voltage (in volts)
I = Current (in amperes)
R = Load resistance
The measurement of level with respect to power originated when Alexander Graham Bell invented a unit of measure for sound levels. This unit became known as the 'bel'. One tenth of a bel is called a decibel (dB). The human ear hears sound in a logarithmic manner. So a level of 100 watts to the human ear would sound twice as loud as a level of 10 watts (not 10 times). One decibel increase in sound is approximately the smallest increase in sound level detectable by the human ear.
This unit of measure is now used as the basis for measuring relative power levels in radio, voice and data networks. For the network in FIG. 4 below, the gain of the system becomes:
FIG. 4 Circuit gain and loss
Note that this is a relative measurement. The resulting value is a measure of the power level at point B with reference to the power level at point A (power at B relative to power at A). The resultant is NOT an absolute value.
For example, if for the system shown in FIG. 4 there is an input signal at point A of 1 watt and an output signal at point B of 10 watts, the system gain is:
= 10 decibels
10 Decibels is written as 10 dB. When working with voice, data, and radio equipment, measurements can be made at single points in a system with reference to 1 watt or 1 milliwatt (instead of with reference to a level at another point). The equation then becomes: Level = dBW :
Log (With reference to 1 watt)
Level = dBm :
Log
(With reference to 1 milliwatt)
If measurements are required to be carried out in volts or amperes, then replacing power with:
Log
when RA = RB : Gain = dB 20 A
or:
Gain = dB 10
if RA = RB: Gain = dB 20
Generally, RA will equal RB and the second formula can normally be used.
Voltages are also sometimes given in decibel forms, where they are measured with respect to 1 volt or 1 microvolt i.e., dBV or dBµV respectively.
3.2 Signal Amplification
As the signal travels along a communications channel, its amplitude decreases as the physical medium resists the flow of the electrical or electromagnetic energy. This effect is known as signal attenuation. In electrical signaling, some materials such as copper are more efficient conductors of electrical energy than others. However, all conductors contain impurities that resist the movement of electrons that constitute the electric current. The resistance of the conductors causes some of the electrical energy of the signal to be converted to heat energy as the signal progresses along the cable resulting in a continuous decrease in the electrical signal. The signal attenuation is measured in terms of signal loss per unit length of the cable, typically decibels per kilometer (dB/km).
FIG. 5 Signal attenuation
To allow attenuation, a limit is set for the maximum length of the communications channel. This is to ensure that the attenuated signal arriving at the receiver is of sufficient amplitude to be reliably detected and correctly interpreted. If the channel is longer than this maximum length, amplifiers or repeaters must be used at intervals along the channel to restore the signal to acceptable levels.
FIG. 6 Signal repeaters
Signal attenuation increases as the frequency increases. This causes distortion to practical signals containing a range of frequencies. For example, a digital signal has a very sharp, fast rising edge to the pulse, which contributes a very high frequency component. The sharper (faster) the rise, the higher will be the frequency component.
This is illustrated in FIG. 5 where the rise-times of the attenuated signals progressively decrease as the signal travels through the channel, caused by the greater attenuation of the high frequency components. This problem can be overcome by the use of special amplifiers referred to as equalizers, which amplify the higher frequencies caused by greater attenuation.
Light also attenuates through glass for much the same reasons as mentioned above. Electromagnetic energy (light) is absorbed by natural resistance properties of glass.
3.3 Channel Bandwidth
The quantity of information a channel can convey over a given period is determined by its ability to handle the rate of change of the signal, that is, its frequency. An analog signal varies between a minimum and maximum frequency and the difference between those frequencies is the bandwidth of that signal. The bandwidth of an analog channel is the difference between the highest and lowest frequencies that can be reliably received over the channel. These frequencies are often those at which the signal has fallen to half the power relative to the mid band frequencies, or the frequency levels at the input to the channel, referred to as 3 dB points. In which case, the bandwidth is known as the 3 dB bandwidth.
FIG. 7 Channel bandwidth
Digital signals are made up of a large number of frequency components, but only those within the bandwidth of the channel will be able to be received. The larger the bandwidth of the channel, the higher the data transfer rate can be and more high frequency components of the digital signal can be transported, and so a more accurate reproduction of the transmitted signal can be received and decoded.
FIG. 8 Effect of channel bandwidth on digital signals
The maximum data transfer rate (C) of the transmission channel can be determined from its bandwidth, by use of the following formula derived by the mathematician, Nyquist.
C= 2 B log2 M bps
where: B is the bandwidth in hertz M levels are used for each signaling element.
In the special case where only two levels, 'ON' and 'OFF' are used (binary) then: M = 2 and C = 2B.
As an example, the maximum Nyquist data transfer rate for a PSTN channel of bandwidth 3100 hertz carrying a binary signal would be 2 × 3100 = 6200 bps. The achievable data transfer rate is reduced in practical situations because of the presence of noise on the channel.
3.4 Noise
As the signals pass through a communications channel the atomic particles and molecules in the transmission medium vibrate and emit random electromagnetic signals as noise. The strength of the transmitted signal is normally large relative to the noise signal. However, as the signal travels through the channel and is attenuated, its level can approach that of the noise. When the wanted signal is not significantly higher than the background noise, the receiver cannot separate the data from the noise and communication errors occur.
An important parameter of the channel is the ratio of the power of the received signal (S) to the power of the noise signal (N). The ratio S/N is called the signal to noise ratio, which is normally expressed in decibels, abbreviated to dB,
S/N = 10 log 10(S/N) dB
where: S = signal power in watts N = noise power in watts A high signal to noise ratio means the wanted signal power is high compared to the noise level, resulting in good quality signal reception. The theoretical maximum data transfer rate for a practical channel can be calculated using the Shannon-Hartley Law, which states:
C = B log2 (1 + S/N) bps
where: C is the data rate in bps B is the bandwidth of the channel in hertz S is the signal power in watts N is the noise power in watts
It can be seen from this formula that increasing the bandwidth or increasing the signal to noise ratio will allow increases to the data rate, and that a relatively small increase in bandwidth is equivalent to a much greater increase in signal to noise ratio. Digital transmission channels make use of higher bandwidths and digital repeaters or regenerators to regenerate the signals at regular intervals and maintain acceptable signal to noise ratios. The degraded signals received at the regenerator are detected, then retimed and retransmitted as nearly perfect replicas of the original digital signals, as shown in FIG. 9. There is no accumulated noise on the signal, even when transmitted thousands of kilometers, provided reasonably good signal to noise ratios are maintained.
FIG. 9 Digital link [Line Driver Digital Repeater Line Receiver Channel,
Channel Degraded Signal Received Regenerated Signal]
4. Data Transmission Modes
4.1 Direction of Signal Flow
Simplex A simplex channel is unidirectional that allows data to flow in one direction only, as shown in FIG. 10. Public radio broadcasting is an example of a simplex transmission.
The radio station transmits the broadcast program, but does not receive any signals back from your radio receiver.
FIG. 10 Simplex transmission
This has limited use for data transfer purposes, as we invariably require the flow of data in both directions to control the transfer process, acknowledge data etc.
Half-duplex
Half-duplex transmission allows us to provide simplex communication in both directions over a single channel, as shown in FIG. 11. Here the transmitter at station 'A' sends data to a receiver at station 'B'. A line turnaround procedure takes place whenever transmission is required in the opposite direction. The station 'B' transmitter is then enabled and communicates with the receiver at station 'A'. The delay in the line turnaround procedures reduces the available data throughout the communications channel.
FIG. 11 Half-duplex transmission
Full-duplex A full-duplex channel gives simultaneous communications in both directions, as shown in FIG. 12.
FIG. 12 Full-duplex transmission
4.2 Sync of digital data signals
Data communications depends on the timing of the signal generation and reception being kept correct throughout the message transmission. The receiver needs to look at the incoming data at the correct instants before determining whether a '1' or '0' was transmitted. The process of selecting and maintaining these sampling times is called synchronization. In order to synchronize their transmissions, the transmitting and receiving devices need to agree on the length of the code elements to be used, known as the bit time. The receiver needs to extract the transmitted clock signal encoded into the received data stream. By synchronizing the bit time of the receiver's clock with that encoded into the data by the sender, the receiver is able to determine the right times to detect (sample) the data transitions in the message and correctly receive the message. The devices at both ends of a digital channel can synchronize themselves using either asynchronous or synchronous transmission as outlined below.
4.3 Asynchronous data transmission
Here, the transmitter and receiver operate independently and exchange a synchronizing bit pattern at the start of each message code element (frame). There is no fixed relationship between one message frame and the next. This is experienced with communication devices such as a computer keyboard input with potentially long random pauses between keystrokes.
FIG. 13 Asynchronous data transmission
The speed setting initially sets the sampling rate before transmission starts (except 'Autobaud' systems). At the receiver the channel is sampled at a high rate, typically in excess of 16 times the bit rate of the data channel, to accurately determine the center of the synchronizing pattern (start bit) and its duration (bit time).
FIG. 14 Clock extraction
The data bits are then determined by the receiver sampling the channel at intervals corresponding to the center of each transmitted bit. These are calculated by counting multiples of the bit time from the center of the start bit. For an eight-bit serial transmission, this sampling is repeated for each of the eight data bits then a final sample is made during the ninth time interval. This sample is to identify the stop bit and confirm that the synchronization has been maintained to the end of the message frame. FIG. 15 illustrates the asynchronous data reception process.
FIG. 15 Asynchronous data reception
4.4 Synchronous transmission
The transmitter and receiver here establish an initial synchronization then continuously transmit data maintaining their synchronization throughout the transmission. This is achieved by special data coding schemes, such as Manchester Encoding, which ensure continuous encoding of the transmitted clock into the transmitted data stream. This enables the synchronization to be maintained at the receiver right to the last bit of the message, which could be as large as 4500 bytes (36 000 bits) long. This allows larger frames of data to be efficiently transferred at higher data rates. The synchronous system packs many characters together and sends them as a continuous stream, called a block.
For each transmission block there is a preamble, containing the start delimiter for initial synchronization purposes and information about the block, and a post-amble, to give error checking etc. An example of a synchronous transmission block is shown in FIG. 16.
FIG. 16 Synchronous transmission block
5. Light
In modern physics, light is represented by either electromagnetic waves or photons.
5.1 Electromagnetic waves
Electromagnetic waves involve a combination of electric and magnetic effects. Consider a static charge. It produces an electric field around it. If the charge is moving, it also produces a magnetic field. It has been shown theoretically and experimentally verified that these electric and magnetic fields combine to cause a disturbance that is propagated through space, called a radiated electromagnetic wave. This wave is self propagating since the changing electric field induces a changing magnetic field which then induces a new changing electric field, and so on. Energy is thus being constantly exchanged between the electric and magnetic fields.
When an electromagnetic wave strikes some matter, its electric and magnetic fields cause the charges in the matter to oscillate in the same manner as those in the originating wave. This enables the energy to be transferred through the material with no net transfer of matter. All electromagnetic waves have the following common properties:
• They are produced by moving charges
• They are transverse waves in which the electric and magnetic fields are mutually perpendicular to one another and perpendicular to the direction of propagation of the waves
• They do not require a medium for propagation but can propagate through material with no net transfer of matter
• They all travel at the same relative speed in free space, which is called the speed of light
The behavior of electromagnetic waves is elegantly quantified in Maxwell's equations, but this is beyond the scope of this guide where we will concentrate on practical applications rather than abstract theory.
5.2 Photons
Photons are considered discrete quantities of electromagnetic energy. Planck proposed that energy is radiated in bursts called 'quanta' where the amount of energy is proportional to the frequency. This is expressed by the formula:
Q = h f
Where: h = Planck's constant (6.63 × 10^-34 joule-seconds).
A quantum of light is called a photon. Photons have some characteristics of a particle being both discrete and finite. Light, however, is also a wave as can be shown by diffraction and interference effects. It thus appears that light is both a particle and a wave.
This is contradictory as a particle is finite and discrete while a wave is infinite and continuous. Physicists consider both theories complementary but do not apply them together! This is known as the wave-particle duality of light and both physical models are equally valid and are useful in describing different optical effects. It is interesting to note that there are parts of both models which do not agree.
Light, as photons or waves, travels in free space at approximately 300,000 km/s (3 × 10^8 m/s). Many effects can be best envisaged by representing the light as rays that travel in straight lines between or through optical components. These rays are modified (reflected, diffracted, refracted etc.) at the optical surfaces of these devices. This optical behavior is explained in Section 3.
6. The EM spectrum
All electromagnetic radiation is fundamentally the same, with photons or waves traveling at the speed of light. The properties of this radiation can be measured in different ways: by the frequency of the electromagnetic waves, their wavelength, or the photon energy present. An arrangement of the order of frequencies, wavelengths, or energy of various types of electromagnetic waves is known as electromagnetic spectrum. The frequencies and wavelengths are related by the formula:
Frequency = Velocity/Wavelength
Photon energy can be measured in electron volts (eV), which is the energy gained by an electron moving through a 1 volt electric field. This can be related to the wavelength, in micrometers, by the formula:
Energy (eV) = 1.2406/Wavelength (µm)
The electromagnetic spectrum represents a continuum of frequencies with no distinct lines of separation between the variously named forms of electromagnetic phenomena.
The spectrum is shown in FIG. 17 below.
FIG. 17 Electromagnetic spectrum
6.1 Optical region of spectrum
This is the small part of the spectrum where our fiber optic devices operate, from about 200 nanometers up to 20-micrometer wavelengths. It includes the visible spectrum at wavelengths of around 400 to 700 nanometers and the adjacent infrared and ultraviolet regions. The wavelength used in fiber optic systems is matched to the particular fiber's transmission characteristics. Most optical fibers use silica glass, which is most transparent in the near infrared region, 700 to 1600 nanometers. Plastic fibers operate best at visible wavelengths, non-silica glass fibers are designed to operate at infrared wavelengths, and special grades of silica can be used in the near-ultraviolet region. The properties of these optic fibers are detailed in Section 3.