Signals, Noise, Modulation, and Demodulation
Signals can be:
Analog: Amplitude change continuously with time Digital: are described as discrete and their amplitude maintains constant level for a prescribed period of time. It is called binary level if only two levels are possible called also a pulse
All digital signals are not necessary binary A four level signal is called a quarternary digital signal
FIGURE 22-1
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Electrical signals: (a) sine wave; (b) binary digital signal; signal; (c) quaternary digital signal
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Modulation
Converting information signals to a different form is called modulation, and the reverse process is called demodulation Many of data communication systems utilize both analog and digital systems, since it is often necessary to change the form of the source information Modulate simply means to change, when analog signal is being modulated (information = modulating signal), some property of it is changing proportional to the modulated signal (carrier)
Modulation
Electronic communications systems are analog and digital
Analog systems in which energy is transmitted and received in analog form Digital communications covers digital transmission and digital modulation
Digital transmission sys. require a physical facility between transmitter & receiver
Original signal may be analog or digital
Digital modulation is the transmittal of digitally modulated analog signals between two or more points
Modulating and demodulated signals are digital pulses Carried through the system on an analog signal (carrier) Original source information with digital modulation may be in analog or digital form
FIGURE 22-2 modulation.
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Analog and digital communications systems: (a) analog communications communications system; (b) digital transmission; (c) digital
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FIGURE 22-2(continued) Analog and digital communications systems: (a) analog communications communications system; (b) digital transmission; (c) digital modulation.
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FIGURE 22-2(continued) (c) digital modulation.
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Analog and digital communications systems: (a) analog communications communications system; (b) digital transmission;
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Signal Analysis
A since wave consists of cycles A cycle is one complete variation in the signal A period is the time the waveform takes to complete one cycle (T) and constitutes 360 degrees or (2 Π radians) A since wave can be described in terms of three parameters:
Amplitude: is the magnitude of the signal at any point and measured in voltage or the vertical displacement. The max. voltage is called peak amplitude or voltage (V) Frequency Phase
FIGURE 22-3
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Three sine waves showing amplitude, frequency, and phase
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FIGURE 22-4
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Comparison of two sine waves of different amplitudes and phases phases
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FIGURE 22-5
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Time domain representation of a singlesingle-frequency sine wave
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FIGURE 22-6
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Frequency spectrum (frequency domain representation) of two sine waves
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FIGURE 22-7
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Wave symmetries: (a) even symmetry; (b) odd symmetry; (c) half half--wave symmetry
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FIGURE 22-8
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Waveform for Example 2– 2–1
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Frequency Spectrum and Bandwidth
Frequency Spectrum consists of all the frequencies contained in the waveform and their amplitudes plotted in the frequency domain BW is the range of frequencies contained in the spectrum and is calculated by subtracting the lowest frequency from the highest BW of a communication channel ≥ BW of information signal
FIGURE 22-9
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Frequency spectrum for Example 2– 2–1
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FIGURE 22-10
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VoiceVoice-frequency spectrum and telephone circuit bandwidth
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Electrical Noise and Signal to Noise Ratio
Electrical noise is any undesirable electrical energy that falls within the pass band of the signal The most prevalent and the most interfering noise to data communication are:
Man-made noise called industrial noise Thermal noise is associated to the rapid and random movement of electrons due to thermal agitation Correlated noise is mutually related to signal
Harmonic distortion Intermodulation distortion
Impulse noise is characterized by high amplitude peaks of short duration in the total noise spectrum Signal-to-noise power ratio is the ratio of the signal power to the thermal noise power level S/N (dBm) = 10 log Ps/Pn
FIGURE 22-11
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Effects of noise on a signal: (a) signal without noise; (b) signal with noise
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FIGURE 22-12
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Correlated noise: (a) harmonic distortion; (b) intermodulation intermodulation distortion
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Amplitude Modulation
AM is the process of changing the amplitude of a relatively high frequency carrier signal in proportion to the instantaneous value of the modulating signal (information) Is relatively inexpensive, low quality form of modulation used for commercial broadcasting, CB radio AM modulators are two-input devices, the output produces a modulated wave
FIGURE 22-13
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AM generation
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Angle Modulation
Results whenever the phase angle (θ) of a sinusoidal signal is varied with respect to time Includes both FM and PM where the difference lies in which property of the carrier (frequency or phase) is directly varied by the modulating signal and which property is indirectly varied. If frequency of the carrier is varied directly in accordance with the information (modulating) signal, FM results, otherwise PM results.
FIGURE 22-14
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AngleAngle-modulated wave in the frequency domain
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FIGURE 22-15
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Angle modulation in the time domain: (a) phase changing with with time; (b) frequency changing with time
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FIGURE 22-16 Phase and frequency modulation of a sinesine-wave carrier by a sinesine-wave signal: (a) unmodulated carrier; (b) modulating signal; (c) frequencyfrequency-modulated wave; (d) phasephase-modulated wave
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Information Capacity, Bits, Bit Rate, Baud, and M-Ary encoding
Information theory is a highly theoretical study of the efficient use of bandwidth to propagate information through electronic communication systems It is used to determine the information capacity which is a measure of how much information (number of independent symbols) can be propagated through a communication system and a function of bandwidth and transmission time Binary digit, or bit is the most basic digital symbols that can be used to represent information Information capacity is often convenient to be expressed in bit rate which is the number of bits transmitted during 1 second (bps).
Hartley’s Law
In 1928, Hartley of Bell Telephone Laboratories developed a useful relationship among bandwidth, transmission time, and information capacity I∞Bxt I = information capacity (bps) B = bandwidth (hertz) t = transmission time (seconds)
Shannon’s Formula
In 1948, mathematician Claude E. Shannon developed the Shannon limit for information capacity I = B log ( 1 + S/N ) = 3.32 B log ( 1 + S/N ) I = information capacity (bps) B = bandwidth (hertz) S/N = signal-to-noise power ratio (unitless) 2
10
M-ary Encoding
Derived from the word binary M represents a digit that corresponds to the number of conditions, levels, or combinations possible for a given number of binary variables The number of bits necessary to produce a given number of conditions is expressed as N = log M or 2*N = M N = number of bits necessary M = number of conditions, levels, or combinations possible with N bits 2
Baud and Minimum Bandwidth
Commonly confused with bps Is rate of change of the signal and is the reciprocal of the time of one output signaling element (symbol) which may represent several information bits and could be encoded as change of amplitude, frequency, or phase Bit rate refers to the rate of change of digital information signal Baud is considered less than bit rate
Nyquist’s Formula
Noiseless transmission medium fb = 2 B fb = is the bit rate in bps B = is the ideal Nyquist bandwidth Using multilevel signaling, the Nyquist formulation for channel capacity is: fb = B log2 M → B = fb / B log2 M = fb / N
fb = channel capacity (bps) B = minimum Nyquist bandwidth (hertz) M = number of discrete signal or voltage levels N = number of bits encoded into each signaling element baud = fb / N
FIGURE 22-17
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Simplified block diagram of a digital radio system
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FIGURE 22-18
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Digital amplitude modulation: (a) input binary; (b) output DAM waveform
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FIGURE 22-19
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FSK in the frequency domain
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FIGURE 22-20
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FSK in the time domain: (a) waveform; (b) truth table
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FIGURE 22-20(continued)
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FSK in the time domain: (a) waveform; (b) truth table
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FIGURE 22-21
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Output phase– phase–versus– versus–time relationship for a BPSK modulator
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FIGURE 22-22
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BPSK modulator: (a) truth table; (b) phasor diagram; (c) constellation constellation diagram
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FIGURE 22-23
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QPSK: (a) output phase– phase–versus– versus–time relationship; (b) truth table; (c) constellation
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FIGURE 22-23(continued)
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QPSK: (a) output phase– versus–time relationship; (b) truth table; (c) constellation phase–versus–
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FIGURE 22-24
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8-PSK: (a) output phase– phase–versus– versus–time relationship; (b) truth table; (c) constellation diagram
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FIGURE 22-24(continued)
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8-PSK: (a) output phase– phase–versus– versus–time relationship; (b) truth table; (c) constellation diagram
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FIGURE 22-25
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1616-PSK: (a) truth table; (b) constellation diagram
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FIGURE 22-26
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8-QAM: (a) output phase– phase–versusversus-time relationship; (b) truth table; (c) constellation diagram
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FIGURE 22-26(continued)
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8-QAM: (a) output phase– phase–versusversus-time relationship; (b) truth table; (c) constellation diagram
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FIGURE 22-27
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1616-QAM modulator: (a) truth table; (b) constellation diagram
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