Data and Computer Communications by William Stallings Eighth Edition Data Transmission Click to edit Master subtitle style Networks and Communication Department.

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Data and Computer Communications by William Stallings Eighth Edition Data Transmission Click to edit Master subtitle style Networks and Communication Department Chapter 3 1

Transmission Terminology Data transmission occurs between a transmitter & receiver via some medium

Types of communications direct link : no intermediate devices. Types of communications: 1) point-to-point : direct link, only 2 devices share link 2) Point –to- multipoint : more than two devices share the link, one sender and multiple recipients. eg: voice conferencing, one person will be talking but many others can listen. 3) Simplex : only in one direction, there is one sender and one receiver; the sender and receiver cannot change roles. eg. Television,. 4) half duplex : either direction, but only one way at a time, eg. police radio, A walkie-talkie 5) full duplex : both directions at the same time, eg. telephone

Frequency, Spectrum and Bandwidth Time domain concepts  analog signal various in a smooth way over time  digital signal maintains a constant level then changes to another constant level  periodic signal pattern repeated over time  aperiodic signal pattern not repeated over time

Analogue & Digital Signals

Periodic Signals

Sine Wave peak amplitude (A)  maximum strength of signal  volts frequency (f)  rate of change of signal  Hertz (Hz) or cycles per second  period = time for one repetition (T)  T = 1/f phase (  )  relative position in time

Varying Sine Waves s(t) = A sin(2  ft +  )

Wavelength ( ) is distance occupied by one cycle b, or, put another way, the distance between two points of corresponding phase of two consecutive cycles. assuming signal velocity v have = vT or equivalently f = v  especially when v=c  c = 3*10 8 ms -1 (speed of light in free space)

Wavelength ( )

Frequency Domain Concepts signal are made up of many frequencies components are sine waves Fourier analysis can shown that any signal is made up of component sine waves can plot frequency domain functions

Addition of Frequency Components (T=1/f) c is sum of f & 3f     

Spectrum & Bandwidth spectrum  range of frequencies contained in signal, eg: Fig 3.4c, it extends from f to 3f. absolute bandwidth  width of spectrum, eg : 2f in Fig 3.4c DC Component  component of zero frequency

DC Component DC component =1 Nonzero average amplitude No DC component, Average amplitude of zero

Frequency Domain Representations freq domain function of Fig 3.4c

Data Rate and Bandwidth  Data rate: is the amount of data that is moved from one place to another in a given time. (bps), Data rate=2*f  Effective bandwidth(or bandwidth ): is the actual speed at which data can be transmitted on a connection.  any transmission system has a limited band of frequencies  this limits the data rate that can be carried  square have infinite bandwidth.  limited bandwidth increases distortion  have a direct relationship between data rate & bandwidth

Sine Waves s(t) = A sin(2  ft +  )

Figure 3.7 (a) & (b)

Data Rate Calculation Suppose that we are using a digital transmission system that is capable of transmitting signals with a bandwidth of 4 MHz. Let us attempt to transmit a sequence of alternating 1s and 0s as the square wave of Figure.What data rate can be achieved? We look at three cases

Data Rate Calculation Case 1  Bandwidth 4MHz, use the sine wave of Fig. 3-7 (a)  4MHz = 5f – f  f = 1MHz  Data rate = 2 Mbps Case 2  Bandwidth 8MHz, use the sine wave of Fig. 3-7 (a)  8MHz = 5f – f  f = 2MHz  Data rate = 4 Mbps Case 3  Bandwidth 4MHz, use the sine wave of Fig. 3-4 (c)  4MHz = 3f – f  f = 2MHz  Data rate = 4 Mbps

Data Rate vs. Bandwidth Bandwidth ↑  Data rate ↑ (compare case 1 & 2)  Same signal quality Same bandwidth  Higher signal quality  lower data rate  Compare case 1 & 3 Same data rate  Bandwidth ↑  better signal quality  Compare case 2 & 3

Data Rate vs. Bandwidth In general,  any digital waveform will have infinite bandwidth. If we attempt to transmit this waveform as a signal over any medium, the transmission system will limit the bandwidth that can be transmitted.  greater the bandwidth transmitted, the greater the cost.  limiting the bandwidth creates distortions, and the greater the potential for error by the receiver.

Effect of bandwidth on a digital signal  greater the bandwidth transmitted, the greater the quality and accuracy.

Transmission Impairments signal received may differ from signal transmitted causing:  analog - degradation of signal quality  digital - bit errors most significant impairments are  attenuation and attenuation distortion  delay distortion  noise

Attenuation  where signal strength falls off with distance depends on medium  Attenuation introduces three considerations for the transmission engineer: 1- strong enough to be detected 2-sufficiently higher than noise to receive without error 3-attenuation varies with frequency, for analog signals Db=10 log 10 (Ps/Pd) Ps is the signal power at the transmitting end (source) of a communications circuit and Pd is the signal power at the receiving end (destination), Ps > Pd.

Attenuation o The first and second problems are dealt with by attention to signal strength and the use of amplifiers or repeaters o To overcome the third problem, techniques are available for equalizing attenuation across a band of frequencies.

Delay Distortion only occurs in guided media propagation velocity varies with frequency hence various frequency components arrive at different times particularly critical for digital signals Equalizing techniques can also be used for delay distortion

Delay Distortion

Noise Noise :additional signals inserted between transmitter and receiver. 1- Thermal noise  due to thermal agitation of electrons  uniformly distributed  white noise  N0=KT(W/Hz) N0 = noise power density in watts per 1 Hz of bandwidth k = Boltzmann’s constant = 1.38 * J/K T = temperature, in Kelvin

Noise 2- Intermodulation noise When signals at different frequencies share the same transmission medium, the result may be intermodulation noise. The effect of intermodulation noise is to produce signals at a frequency that is the sum or difference of the two original frequencies or multiples of those frequencies, thus possibly interfering with services at these frequencies. It is produced by nonlinearities in the transmitter, receiver, and/or intervening transmission medium.

Noise 3-crosstalk an unwanted coupling between signal paths. It can occur by electrical coupling between nearby twisted pairs or, rarely, coax cable lines carrying multiple signals. It can also occur when microwave antennas pick up unwanted signals 4-Impulse noise  irregular pulses or spikes eg. external electromagnetic interference  short duration  high amplitude  a minor annoyance for analog signals  but a major source of error in digital data a noise spike could corrupt many bits

Channel Capacity max possible data rate on comms channel is a function of:  Data rate, in bits per second (bps), at which data can be communicated  Bandwidth, as constrained by the transmitter and the nature of the transmission medium, expressed in cycles per second, or Hertz  Noise, average level of noise over the communications path  Error rate, at which errors occur, where an error is the reception of a 1 when a 0 was transmitted or the reception of a 0 when a 1 was transmitted limitations due to physical properties want most efficient use of capacity

Nyquist Bandwidth consider noise free channels if rate of signal transmission is 2B then can carry signal with frequencies no greater than B  ie. given bandwidth B, highest signal rate is 2B for binary signals, 2B bps needs bandwidth B Hz For multilevel,can increase rate by using M signal levels Nyquist Formula is: C = 2B log 2 M so increase rate by increasing signals  at cost of receiver complexity  limited by noise & other impairments

Shannon Capacity Formula consider relation of data rate, noise & error rate  faster data rate shortens each bit so bursts of noise affects more bits  given noise level, higher rates means higher errors Shannon developed formula relating these to signal to noise ratio (in decibels) SNR db = 10 log 10 (signal/noise) Capacity C=B log 2 (1+SNR)  theoretical maximum capacity  get lower in practise

Shannon Capacity Formula

Summary data transmission Time domain and Frequency domain transmission impairments