Data Communications and Networks Abdul-Rahman Mahmood http://alphapeeler.sourceforge.net http://pk.linkedin.com/in/armahmood abdulmahmood-sss twitter.com/alphapeeler alphapeeler.sourceforge.net/pubkeys/pkey.htm VC++, VB, ASP
Data Transmission Toto, I've got a feeling we're not in Kansas anymore. Judy Garland in The Wizard of Oz The successful transmission of data depends principally on two factors: the quality of the signal being transmitted and the characteristics of the transmission medium. The objective of this chapter and the next is to provide the reader with an intuitive feeling for the nature of these two factors.
Transmission Terminology data transmission occurs between a transmitter & receiver via some medium guided medium eg. twisted pair, coaxial cable, optical fiber unguided / wireless medium eg. air, water, vacuum
Transmission Terminology direct link no intermediate devices point-to-point direct link only 2 devices share link multi-point more than two devices share the link
Transmission Terminology simplex one direction eg. television half duplex either direction, but only one way at a time eg. police radio 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 Mathematically, a signal s(t) is defined to be periodic if and only if s(t + T) = s(t) -00 < t < +00 where the constant T is the period of the signal (T is the smallest value that satisfies the equation). Otherwise, a signal is aperiodic.
Sine Wave peak amplitude (A) maximum strength of signal volts frequency (f) rate of change of signal Hertz (Hz) or cycles per second period 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 between two points of corresponding phase in two consecutive cycles assuming signal velocity v have or equivalently f = v especially when v=c = vt c = 3*10 8 ms -1 (speed of light in free space)
Frequency Domain Concepts electromagnetic signal are made up of many frequencies When all of the frequency components of a signal are integer multiples of one frequency, the latter frequency is referred to as the fundamental frequency. Fourier analysis can shown that any signal is made up of component sine waves The period of the total signal is equal to the period of the fundamental frequency. The period of the component sin(2 ft) is T = 1/f and the period of s(t) is also T, as can be seen from next Figure.
Addition of Frequency Components (T=1/f) c is sum of f & 3f
We can say that for each signal, there is a time domain function s(t) that specifies the amplitude of the signal at each instant in time. Similarly, there is a frequency domain function S(f) that specifies the peak amplitude of the constituent frequencies of the signal.
Frequency Domain Representations freq domain func of Fig 3.4c freq domain func of single square pulse
Spectrum & Bandwidth spectrum range of frequencies contained in signal absolute bandwidth width of spectrum effective bandwidth often just bandwidth narrow band of frequencies containing most energy DC Component component of zero frequency
frequency components of the square wave Consider Fig.3.2b Positive pulse = 0 and Negative pulse =1. waveform represents binary stream 0101.. If T = 1/(2f ); Then data rate = 2f bps What are the frequency components of this signal? To answer this question, consider again Figure 3.4. By adding together sine waves at frequencies f and 3f, we get a waveform that begins to resemble the original square wave. Let us continue this process by adding a sine wave of frequency 5f, as shown in Figure 3.7a, and then adding a sine wave of frequency 7f, as shown in Figure 3.7b.As we add additional odd multiples of f, suitably scaled, the resulting waveform approaches that of a square wave more and more closely. Frequency components of the square wave with amplitudes A :
Data Rate and Bandwidth any transmission system has a limited band of frequencies this limits the data rate that can be carried (digital) square have infinite components and hence bandwidth but most energy in first few components If we attempt to transmit this waveform as a signal over any medium, the transmission system will limit the bandwidth that can be transmitted For any given medium, Bandwidth Cost Bandwidth distortion Bandwidth error by the receiver Bandwidth data rate
Data Rate and Bandwidth Case I. f = 10^6 cycles/second = 1 MHz, of signal is : Bandwidth= = (5 X 10^6) 10^6 = 4 MHz* CASE I. Bandwidth = 4 MHz; data rate = 2 Mbps CASE II. Bandwidth = 8 MHz; data rate = 4 Mbps CASEIII. Bandwidth = 4 MHz; data rate = 4 Mbps Conclusion : higher the center frequency, the higher the potential bandwidth and therefore the higher the potential data rate.
Analog and Digital Data Transmission data as entities that convey meaning, or information signals electric or electromagnetic representations of data, physically propagates along medium signaling Signaling is the physical propagation of the signal along a suitable medium transmission Transmission communication of data by propagation and processing of signals In what follows, we try to make these abstract concepts clear by discussing the terms analog and digital as applied to data, signals, and transmission.
Acoustic Spectrum (Analog)
Video Interlaced Signaling
Text Code IRA, Attenuation Most popular example is Morse code. International Reference Alphabet (IRA). Each character in this code is represented by a unique 7-bit pattern; 128 different characters IRA-encoded characters are stored and transmitted using 8 bits/character. The eighth bit is a parity bit used for error detection. This bit is set such that the total number of binary 1s in each octet is always odd (odd parity) or always even (even parity).thus a transmission error that changes a single bit, or any odd number of bits, can be detected. Digital signaling are generally cheaper than analog signaling and is less susceptible to noise interference. The disadvantage is that digital signals suffer more from attenuation than do analog signals.
Audio Signals Frequency components of typical speech may be found between 100 Hz and 7 khz. easily converted into electromagnetic signals varying volume converted to varying voltage Telephone handset limits frequency range for voice channel to 300-3400Hz (within range 100Hz 7KHz)
Video Signals USA - 483 lines per frame, at frames per sec have 525 lines but 42 lost during vertical retrace 525 lines x 30 scans per /sec = 15750 lines per sec 63.5 s per line 11 s for retrace, so 52.5 s per video line max frequency if line alternates black and white horizontal resolution is about 450 lines giving 225 cycles of wave in 52.5 s max frequency of 4.2MHz
Digital Data as generated by computers etc. has two dc components : 0 and 1 bandwidth depends on data rate
Analog Signals
Digital Signals
Advantages & Disadvantages of Digital Signals cheaper less susceptible to noise but greater attenuation digital now preferred choice
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 received signal strength must be: strong enough to be detected sufficiently higher than noise to receive without error so increase strength using amplifiers/repeaters is also an increasing function of frequency so equalize attenuation across band of frequencies used eg. using loading coils or amplifiers For any other frequency f, the relative attenuation in decibels is A 1000-Hz tone of a given power level is applied to the input, and the power P 1000, is measured at the output.
Delay Distortion only occurs in guided media Occurs because propagation of a signal velocity varies with frequency hence various frequency components arrive at different times resulting in phase shifts particularly critical for digital data intersymbol interference : some of the signal components of one bit position will spill over into other bit positions, causing intersymbol interference.
Noise additional signals inserted between transmitter and receiver (1) Thermal due to thermal agitation of electrons uniformly distributed white noise N o = kt(w/hz) N o = noise power density in watts per 1 Hz of bandwidth k = Boltzmann s constant = 1.38 * 10-23 J/K T = temperature, in kelvins EXAMPLE 3.1 Room temperature is usually specified as T = 17 C, or 290 K. At this temperature, the thermal noise power density is N 0 = (1.38 X 10-23 ) X 290 = 4 X 10-21 W/Hz = -204 dbw/hz where dbw is the decibel-watt, defined in Appendix 3A. The noise is assumed to be independent of frequency. Thus the thermal noise in watts present in a bandwidth of B Hertz can be expressed as N = ktb or, in decibel-watts : N = 10 log k + 10 log T + 10 log B = -228.6 dbw + 10 log T + 10 log B EXAMPLE 3.2 Given a receiver with an effective noise temperature of 294 K and a 10-MHz bandwidth, the thermal noise level at the receiver s output is N = -228.6 dbw + 10 log12942 + 10 log 107 = -228.6 + 24.7 + 70 = -133.9 dbw
Noise (2) Intermodulation When signals at different frequencies share the same transmission medium, the result may be intermodulation noise (3)crosstalk a signal from one line is picked up by another (4)impulse 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
Effect of noise on a digital signal
Channel Capacity Channel Capacity is the max possible data rate on communication channel is a function of data rate - in bits per second bandwidth - in cycles per second or Hertz noise - on comms link error rate - of corrupted bits limitations are due to physical properties of medium we would like to make as efficient use as possible of a given bandwidth. The main constraint on achieving this efficiency is noise
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 can increase rate by using M signal levels (voltage) Nyquist Formula is: C = 2B log 2 M so increase rate by increasing signals EXAMPLE 3.3 Consider a voice channel being used, via modem, to transmit digital data. Assume B=3100 Hz, M=8. Then the Nyquist capacity, C, of the channel is C= 2Blog 2 M = 2X3100 log 2 8 = 6200 X 3 = 18,600 bps Online calculator : http://web2.0calc.com/
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
Summary looked at data transmission issues frequency, spectrum & bandwidth analog vs digital signals transmission impairments