Data Communication Concepts I

DATA COMMUNICATION FUNDAMENTALS

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A SIMPLIFIED COMMUNICATION MODEL

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Analog vs Digital Transmission Terminology • Analog data take on continuous values in a given interval, e.g. audio (human speech) or video. • Digital data take on discrete values, e.g. text or integers. • Signals are electromagnetic representations of data. • Signaling is the physical propagation of the signal along a suitable medium. • Transmission is the communication of data by the propagation and processing of signals. 3

• An analog signal is a continuously varying electromagnetic wave. • Used in early telephone systems. • Analog signals had the drawback that they attenuate (weaken) over long distances. Needed amplifiers to boost the signals. However, amplifiers distort the signal and introduce noise. • A digital signal is a sequence of binary voltage pulses (0’s and 1’s). • Digital transmission avoids the noise problem by encoding the analog signal into digital form. The digitized version is then sent across the network. 4

Analog vs Digital, cont. • The original analog signal is then recreated at the receiving end. The signal is propagated over longer distances by the use of repeaters. • A repeater receives the signal, reconstructs the pattern of 0’s and 1’s, then retransmits the new signal.

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Why Digital? • Ease with which digital signals are generated compared to analog. • Digital signals are subject to less distortion and interference than are analog signals. • Easier to detect and correct errors in digital data. • Digital circuits are : – more reliable – more flexible – cheaper 6

Data Encoding Both analog and digital data can be encoded as either analog or digital signals. • Digital Data -> Digital Signals The simplest form of encoding digital data is to assign one voltage level to binary 1 and another to binary 0. For e.g. A sending device might use a negative voltage (-V) to represent a binary 1 and a positive voltage (+V) to represent a binary 0. The receiving device senses the voltage and interprets a +V as a binary 0 and a -V as binary 1. 7

Transmission of Binary Data:

In reality the transmitted signals are attenuated (reduced) and distorted by the transmission medium. 8

The extent of attenuation and distortion is strongly influenced by: • the type of transmission medium • the bit rate of the transmitted data • the distance between the 2 communicating devices. The simplest encoding scheme is the Non-Returnto-Zero (NRZ) scheme, -V => binary 1 and +V => binary 0. More complex encoding schemes are used to improve performance. For e.g. Manchester encoding scheme. Binary 1 encoded as low-high signal. Binary 0 encoded as a high-low signal. 9

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Analog Data -> Digital Signals • Analog data are often digitized in order to be transmitted via digital transmission facilities. Pulse Code Modulation (PCM ) is a technique used for this. • A codec (coder -decoder)converts analog signals to digital data - used mainly for voice data. • The transmission of data across a long distance requires a modulator at one end to modulate the signal, i.e. modify the carrier wave. A demodulator is required at the other end to demodulate or reproduce the original signal. A modem is a device which performs modulation and 11 demodulation functions.

Terminology • Attenuation - a measure of how much loss a signal experiences when it travels down a communication medium. • Amplitude - the strength of the signal (expressed as volts or decibels). • Baud Rate - a measure of the number of line changes which occur every second. For binary signal, this is expressed in bits per second (bps). If each signal represents 1 bit, baud is the same as bps. When each signal represents more than one bit, baud does not = bps. More precise to refer to it as the symbol rate. 12

• Noise - background interference. Noise makes it impossible to achieve the maximum transmission rate of a system. • Frequency - The rate of change the signal undergoes every second, (expressed in Hertz (Hz) or cycles per second. A 30 Hz signal changes 30 times a second.

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Frequency, cont.

A cycle is one complete movement of the wave from its original position and back to the same point again. The number of cycles (waves) per second is called Hertz. 14

• Bandwidth - the frequency range (or spectrum) of a signal. It is measured as the difference between the highest and lowest frequencies. • The maximum rate at which the hardware can change a signal is known as its effective bandwidth. Bandwidth is measured in cycles per second or Hertz. • The capacity of the channel is related to the effective bandwidth and is measured in bits per second. 15

Relationship between Data Rate and Bandwidth In the 1924 H. Nyquist discovered a fundamental relationship between the bandwidth of a system and the maximum number of bits per second that can be transmitted over that system. It is called the Nyquist Sampling Theorem which states that: the maximum data rate in bits per second that can be achieved over a transmission system of bandwidth B is 2B. 16

E.g. A voice channel is used to transmit data via modem. Assuming a bandwidth of 3100 Hz, then the transmission capacity of the channel (i.e. the maximum data rate) is 2B = 6200 bps. The above formula is based on the assumption that the channel is noiseless and the transmission system uses 2 voltage levels - one bit for each signal element. If the system uses K possible values for voltage, instead of two, Nyquist’s theorem states that the maximum data rate possible, in bits per second is: D = 2Blog2K 17

Nyquist’s formula provides an absolute maximum that cannot be achieved in practice. Noise is inherent in real communication systems, making impossible to achieve the theoretical maximum data rate. •In 1948, Claude Shannon extended Nyquist’s work to specify the maximum data rate that can be achieved over a transmission system that introduces noise. Shannon’s theorem states that: C = Blog2(1 + S/N) where C is the effective channel capacity B is the hardware bandwidth, S is the average signal power and N is the average noise power. 18

• The term S/N is called as the signal-to-noise ratio. • It is not represented directly. Instead, engineers use the quantity 10log10S/N, which is measured in decibels (dB). For e.g. a S/N ratio of 100 is represented as 20 dB and a ratio of 1000 is represented as 30 dB. • In practice, Shannon’s theorem determines how fast one can send data across a voice telephone call. 19

Application of Shannon’s theorem: Voice telephone system has a S/N ratio of ~ 30dB and a bandwidth of approximately 3000 Hz. The max. no. of bits that can be transmitted across such a system is limited to: c = 3000 log2(1 + 1000) i.e. approximately 30,000 bps (30kbps). Faster transmission will only be possible after the S/N ratio is improved. 20