Communication2 Lecture 1 Overview • Introduction – Communication systems – Digital communication system – Importance of Digital transmission • Basic Concepts in Signals – Sampling – Quantization – Coding Digital Communication Meshal Abdullah Al- What is Communication? • Communication is transferring data reliably from one point to another – Data could be: voice, video, codes etc… • It is important to receive information that was sent transmitter. • Communication system the same from the – A system that allows transfer of information realiably Digital Communication Meshal Abdullah Al- Communication Systems Transmitter Source “Sending Point” Communication System Digital Communication Meshal Abdullah Al- Receiver Sink “Receiving Point” Information Source Transmitter Receiver Channel Block Diagram of a typical communication system Digital Communication Meshal Abdullah Al- Information Sink • Information Source – The source of data • Data could be: human voice, data storage device CD, video etc.. – Data types: • Discrete: Finite set of outcomes “Digital” • Continuous : Infinite set of outcomes “Analog” • Transmitter – Converts the source data into a suitable form for transmission through signal processing – Data form depends on the channel Digital Communication Meshal Abdullah Al- • Channel: – The physical medium used to send the signal – The medium where the signal propagates till arriving to the receiver – Physical Mediums (Channels): • Wired : twisted pairs, coaxial cable, fiber optics • Wireless: Air, vacuum and water – Each physical channel has a certain limited range of frequencies ,( fmin fmax ), that is called the channel bandwidth – Physical channels have another important limitation which is the NOISE Digital Communication Meshal Abdullah Al- • Channel: • Noise is undesired random signal that corrupts the original signal and degrades it • Noise sources: » Electronic equipments in the communication system » Thermal noise » Atmospheric electromagnetic noise (Interference with another signals that are being transmitted at the same channel) – Another Limitation of noise is the attenuation • Weakens the signal strength as it travels over the transmission medium • Attenuation increases as frequency increases – One Last important limitation is the delay distortion • Mainly in the wired transmission • Delays the transmitted signals Violates the reliability of the communication system Digital Communication Meshal Abdullah Al- • Receiver – Extracting the message/code in the received signal • Example – Speech signal at transmitter is converted into electromagnetic waves to travel over the channel – Once the electromagnetic waves are received properly, the receiver converts it back to a speech form – Information Sink • The final stage • The user Digital Communication Meshal Abdullah Al- Digital Communication Abdullah Al- Effect of Noise On a transmitted signal Meshal Digital Communication System • Data of a digital format “i.e binary numbers” Information Source A/D Converter Source Encoder Channel Encoder Modulator Channel Information Sink D/A Converter Source Decoder Digital Communication Meshal Channel Decoder Abdullah Al- Demodulator • Information source – Analog Data: Microphone, speech signal, image, video etc… – Discrete (Digital) Data: keyboard, binary numbers, hex numbers, etc… • Analog to Digital Converter (A/D) – Sampling: • Converting continuous time signal to a digital signal – Quantization: • Converting the amplitude of the analog signal to a digital value – Coding: • Assigning a binary code to each finite amplitude in the analog signal Digital Communication Meshal Abdullah Al- • Source encoder – Represent the transmitted data more efficiently and remove redundant information • How? “write Vs. rite” • Speech signals frequency and human ear “20 kHz” – Two types of encoding: – Lossless data compression (encoding) • Data can be recovered without any missing information – Lossy data compression (encoding) • Smaller size of data • Data removed in encoding can not be recovered again Digital Communication Meshal Abdullah Al- • Channel encoder: – To control the noise and to detect and correct the errors that can occur in the transmitted data due the noise. • Modulator: – Represent the data in a form to make it compatible with the channel • Carrier signal “high frequency signal” • Demodulator: – Removes the carrier signal and reverse the process of theDigital Modulator Communication Abdullah AlMeshal • Channel decoder: – Detects and corrects the errors in the signal gained from the channel • Source decoder: – Decompresses the data into it’s original format. • Digital to Analog Converter: – Reverses the operation of the A/D – Needs techniques and knowledge about sampling, quantization, and coding methods. • Information Sink – The User Digital Communication Meshal Abdullah Al- Why should we use digital communication? • Ease of regeneration – Pulses “ 0 , 1” – Easy to use repeaters • Noise immunity – Better noise handling when using repeaters that repeats the original signal – Easy to differentiate between the values “either 0 or 1” • Ease of Transmission – Less errors – Faster ! – Better productivity Digital Communication Meshal Abdullah Al- Why should we use digital communication? • Ease of multiplexing – Transmitting several signals simultaneously • Use of modern technology – Less cost ! • Ease of encryption – Security and privacy guarantee – Handles most of the encryption techniques Digital Communication Meshal Abdullah Al- Disadvantage ! • The major disadvantage of digital transmission is that it requires a greater transmission bandwidth or channel bandwidth to communicate the same information in digital format as compared to analog format. • Another disadvantage of digital transmission is that digital detection requires system synchronization, whereas analog signals generally have no such requirement. Digital Communication Meshal Abdullah Al- Chapter 2: Analog to Digital Conversion (A/D) Abdullah Al-Meshal Digital Communication System Information Source A/D Converter Source Encoder Channel Encoder Modulator Channel Information Sink D/A Converter Source Decoder Channel Decoder Demodulator 2.1 Basic Concepts in Signals • A/D is the process of converting an analog signal to digital signal, in order to transmit it through a digital communication system. • Electric Signals can be represented either in Time domain or frequency domain. – Time domain i.e v(t) 2sin( 21000t 45) – We can get the value of that signal at any time (t) by substituting in the v(t) equation. Time domain Vs. Frequency domain Fourier/Laplace Transform Time Domain Frequency Domain Inverse Fourier / Inverse Laplace Transform Time domain Vs. Frequency domain • Consider taking two types of images of a person: • Passport image • X-Ray image • Two different domains, spatial domain “passport image” and “X-Ray domain”. • Doctors are taking the image in the X-Ray domain to extract more information about the patient. • Different domains helps fetching and gaining knowledge about an object. – An Object : Electric signal, human body, etc… Time domain Vs Frequency domain • We deal with communication system in the time domain. – Lack of information about the signal – Complex analysis • Frequency domain gives us the ability to extract more information about the signal while simplifying the mathematical analysis. Frequency Domain • To study the signal in the frequency domain, we need to transfer the original signal from the time domain into the frequency domain. – Using Fourier Transform X( f ) x(t)e j 2 ft dt Fourier Transform Time domain Frequency Domain x(t) X( f )e j 2ft df Inverse Fourier Transform Frequency domain Time Domain Spectrum • The spectrum of a signal is a plot which shows how the signal amplitude or power is distributed as a function of frequency. X( f ) x(t)e j 2 ft dt 0.5 e j 2ft dt 0.5 1 sin( f ) j 0.5 ft j 0.5 ft e e j2f f Time Domain Frequency Domain Amp. Amp. Time(s) Frequency (Hz) Band limited signals • A band limited signal is a signal who has a finite spectrum. • Most of signal energy in the spectrum is contained in a finite range of frequencies. • After that range, the signal power is almost zero or negligible value. X(f) Symmetrical Signal Positive = Negative - fH + fH Freq. Converting an Analog Signal to a Discrete Signal (A/D) • Can be done through three basic steps: 1- Sampling 2- Quantization 3- Coding Sampling • Process of converting the continuous time signal to a discrete time signal. • Sampling is done by taking “Samples” at specific times spaced regularly. – V(t) is an analog signal – V(nTs) is the sampled signal • Ts = positive real number that represent the spacing of the sampling time • n = sample number integer Sampling Original Analog Signal “Before Sampling” Sampled Analog Signal “After Sampling” Sampling • The closer the Ts value, the closer the sampled signal resemble the original signal. • Note that we have lost some values of the original signal, the parts between each successive samples. • Can we recover these values? And How? • Can we go back from the discrete signal to the original continuous signal? Sampling Theorem • A bandlimited signal having no spectral components above fmax (Hz), can be determined uniquely by values sampled at uniform intervals of Ts seconds, where • An analog signal can be reconstructed from a sampled signal without any loss of information if and only if it is: – Band limited signal – The sampling frequency is at least twice the signal bandwidth 1 Ts 2 f max Quantization • Quantization is a process of approximating a continuous range of values, very large set of possible discrete values, by a relatively small range of values, small set of discrete values. • Continuous range infinte set of values • Discrete range finite set of values Quantization • Dynamic range of a signal – The difference between the highest to lowest value the signal can takes. Quantization • In the Quantization process, the dynamic range of a signal is divided into L amplitude levels denoted by mk, where k = 1, 2, 3, .. L • L is an integer power of 2 • L = 2k • K is the number of bits needed to represent the amplitude level. • For example: – If we divide the dynamic range into 8 levels, • L = 8 = 23 – We need 3 bits to represent each level. Quantization • Example: – Suppose we have an analog signal with the values between [0, 10]. If we divide the signal into four levels. We have • • • • m1 m2 m3 m4 [ 0, 2.5 ] [ 2.5, 5 ] [ 5 , 7.5] [ 7.5, 10] Quantization • For every level, we assign a value for the signal if it falls within the same level. M1 = 1.25 if the signal in m1 M2 = 3.75 if the signal in m2 M3 = 6.25 if the signal in m3 M4 = 8.75 if the signal in m4 Q [ v(t) ] = Quantization Original Analog Signal “Before Quantization” Quantized Analog Signal “After Quantization” Quantization Original Discrete Signal “Before Quantization” Quantized Discrete Signal “After Quantization” Quantization • The more quantization levels we take the smaller the error between the original and quantized signal. • Quantization step Dynamic Range Smax Smin No. of Quantization levels L • The smaller the Δ the smaller the error. Coding • Assigning a binary code to each quantization level. • For example, if we have quantized a signal into 16 levels, the coding process is done as the following: Step Code Step Code Step Code Step Code 0 0000 4 0100 8 1000 12 1100 1 0001 5 0101 9 1001 13 1101 2 0010 6 0110 10 1010 14 1110 3 0011 7 0111 11 1011 15 1111 Coding • The binary codes are represented as pulses • Pulse means 1 • No pulse means 0 • After coding process, the signal is ready to be transmitted through the channel. And Therefore, completing the A/D conversion of an analog signal.
