ECM3501: Principles of Communication Engineering

Transcription

1 ECM3501: Principles of Communication Engineering Po-Ning Chen, Professor Dept. of Communications Eng. National Chiao Tung University Background and Preview To give you a basic understanding of communications

2 Figure-1 Theory The next figure is always the Figure 1 in every book regarding communications. Po-Ning Chen@cm.nctu Background 3 Communications What is communication (or more specifically, communication engineering)? The transmission of information from one point to another through a succession of certain processes. Po-Ning Chen@cm.nctu Background 4

3 Basic Elements Regard Communications Source of information Voice, music, picture, or computer data Po-Ning Background 5 Basic Elements Regard Communications Transmitter Source Source Symbol (i.e., Source Word) Symbolize the information from a source Source Symbol Code Word Encode the source symbol so that the other sources (i.e., noise and interfering signal) can hardly interfere the information transmission. Code Word Channel Symbol (i.e., Transmitted Signals) Modulate the code word into a form that is suitable for transmission over the channel, which involves varying some parameter of a carrier wave in accordance with the message signal. Po-Ning Chen@cm.nctu Background 6

4 Basic Elements Regard Communications Noise/Interference Unwanted waves that tend to disturb the transmission and processing of messages. Could be internal or external to the system. Could be additive or multiplicative (or both) to the information-bearing signals. Po-Ning Background 7 Basic Elements Regard Communications Receiver Hard Decision Channel Symbol Code Bit Decode from Code Bits to Code Word Code Word Source Symbol Source Soft Decision Decode from Channel Symbol to Code Word Code Word Source Symbol Source Po-Ning Chen@cm.nctu Background 8

5 Example: Basic Elements Regard Communications Source = An alphabet A Po-Ning Chen@cm.nctu Background 9 Example : Basic Elements Regard Communications Transmitter Source A Binary Source Symbol ( ) Symbolize the information from a source Source Symbol ( ) Code Word ( ) Encode the source symbol by the three-times repetition code so that the other sources (i.e., noise and interfering signals) can hardly interfere the information transmission. 001,010,011,100,101,110 are not code words. Hence, their appearance is possible only when noise is introduced. Po-Ning Chen@cm.nctu Background 10

6 Example : Basic Elements Regard Communications Code Word ( ) Channel Symbol ( ) Modulate the code word into some channel-permissible (physical-medium permissible) symbols. Due to Channel Interference, we receive: Po-Ning Chen@cm.nctu Background 11 Example : Basic Elements Regard Communications Receiver Hard Decision Channel Symbol Code Bit (Threshold 2.5) Decode from Code Bits to Code Word (Majority Rule) Code Word Source Symbol Source Q Po-Ning Chen@cm.nctu Background 12

7 Example : Basic Elements Regard Communications Receiver Soft Decision Decode from Channel Symbol to (channel-symbolized) Code Word By finding the minimum distance to legitimate codewords 000 and 111. E.g., d(033, 000) = (0 0) 2 +(3 0) 2 +(3 0) 2 = 18 d(033, 555) = (0 5) 2 +(3 5) 2 +(3 5) 2 = 33 Code Word Source Symbol Source A Po-Ning Chen@cm.nctu Background 13 Basic Modes of Communications Broadcasting Often, uni-directional. A single powerful transmitter to numerous (inexpensive) receivers Example. Radio and TV. Point-to-point communication Often, bi-directional. Two entities exchanges information. Example. Telephone. Po-Ning Chen@cm.nctu Background 14

8 Feature Of Communications Statistics The source is statistical in nature. The noise and interference are naturally random. Principles of Communication Engineering: How to design a communication system only based on the knowledge of the statistics of the source and interferences (without knowing exactly what the true source and interference are)? Po-Ning Chen@cm.nctu Background 15 Feature Of Communications Example Source We do not know if the next source symbol is 0 or 1. But, we do know the probability of the next source symbol being 0, and also, the probability of the next source symbol being 1. Noise/Interference We do not know what value the noise/interference will take? But, we do know the noise is, say, Gaussian distributed. Po-Ning Chen@cm.nctu Background 16

9 Feature Of Communications This is the reason why Probabilities (Chapter 1) is considered an important background to communication study. Po-Ning Background 17 Primary Communication Resources Primary Communication Resources are something known at the design stage. As aforementioned, source and noise/interference are (often) something unknown at the design stage. Po-Ning Background 18

10 Primary Communication Resources Examples of Primary Communication Resources Transmitted Power Specifically, averaged power of the transmitted signals. A more useful measure than the absolute transmitted power is the signal-to noise power ratio (SNR), defined as the ratio of the average signal power to the average noise power. This quantity is often expressed in dbs, 10 log 10 (SNR). Channel Bandwidth The band of frequencies for use of transmitting messages. Po-Ning Chen@cm.nctu Background 19 Primary Communication Resources Design principle of a communication system How to efficiently use (in a tradeoff fashion) the communication resources! Po-Ning Chen@cm.nctu Background 20

11 Sources of Information Sources can sometimes be viewed as one kind of Communication Resources. For example, there are systems designed specifically for exchanging voices. Such a system may not be apt to transmit computer data. This introduces the subjects of Source-Specific Communication. Next, we brief several sources commonly seen in the literature. Po-Ning Chen@cm.nctu Background 21 Sources of Information: (1) Speech Features Voice spectrum extends well beyond 10kHz. Most of the average power is concentrated in the range of 100 to 600 Hz. Pitch Name Do Re Mi Fa So La Si Do Freq (Hz) A band of 300 to 3100 Hz gives good articulation. The sound wave propagates through the air at a speed of 300 meter/second. Po-Ning Chen@cm.nctu Background 22

12 Schematic representation of the vocal system Po-Ning Background 23 Sources of Information: (1) Speech The speech-production process may be viewed as a form of filtering: A sound source excites a vocal tract filter. excitation Glottal volume + Vocal tract + + a 1 a 9 D speech Lips + a 10 D Po-Ning Chen@cm.nctu Background 24

13 Sources of Information: (1) Speech As the sound propagates along the vocal tract, the spectrum (i.e., frequency content) is shaped by the frequency selectivity of the vocal tract a resonance phenomenon observed in organ pipe. So the hearing mechanism is (and should be) sensitive to frequency. Po-Ning Chen@cm.nctu Background 25 Source of Information: (2) Music Originate from musical instruments, such as piano, violin and flute. It consists of: Melody: A time sequence of sounds. Harmony: A set of simultaneous sounds. Different from speech, the spectrum of a music source may extend up to about 15 KHz. Accordingly, a much wider bandwidth resource is demanded. Po-Ning Chen@cm.nctu Background 26

14 Source of Information: Pictures Two dimensional information. Classifications Dynamic pictures Video, such as North American Audio TV Still pictures Facsimile. To transmit still picture over a telephone channel. Po-Ning Chen@cm.nctu Background 27 Source of Information: (3) NAA-TV North American Analog TV 525 horizontal lines, decomposed into two line interlaced fields. Completion of each interface field takes 1/60 second Horizontal line-scanning frequency is 262.5/(1/60) = KHz. Hence, 30 still pictures are shown per second. The human persistence of vision phenomenon will perceive these still pictures to be moving pictures. Po-Ning Chen@cm.nctu Background 28

15 Source of Information: (3) NAA-TV Interlaced raster scan. Po-Ning Background 29 Source of Information: (3) NAA-TV In the NTSC (National Television System Committee) system, a total of 4.2 MHz bandwidth is demanded for TV transmission. Po-Ning Chen@cm.nctu Background 30

16 Source of Information: (4) Computer Data The first code developed specifically for computer communication ASCII (American Standard Code for Information Interchange). Po-Ning Background 31 Source of Information: (4) Computer Data Po-Ning Background 32

17 Source of Information: (4) Computer Data ASCII (American standard code for information interchange) Bit originates from Binary Digit. 7-bit code for alphabetic numerical characters Bit 8 is sometimes used as parity-check bit or used to form the extended ASCII code Even parity: Total number of 1 s is even. Odd parity: Total number of 1 s is odd. Extended ASCII code can be displayed, but can not necessarily be printed out. Po-Ning Chen@cm.nctu Background 33 Source of Information: (4) Computer Data Since ASCII is defined for communication, it also includes some symbols for communication purpose, such as ENQ (enquiry) 05X ETB (end of transmission block) 17X Po-Ning Chen@cm.nctu Background 34

18 Source of Information: (4) Computer Data RS (Recommended Standard) -232 Transmission Synchronous Asynchronous Po-Ning Background 35 Source of Information: (4) Computer Data Asynchronous Serial Data No clock or timing signal required. S T : start bit S : stop bit P : parity bit D 6 ~D 0 : data bit (often, exact one ASCII character) Usually, 10 bit frame with even-parity/7-data-bit or no-parity/8-data-bit. frame S ST D0 D1 D2 D3 D4 D5 D6 P S ST D0 D1 D2 D3 D4 D5 D6 P S Po-Ning Chen@cm.nctu Background 36

19 Source of Information: (4) Computer Data Synchronous Serial Data No start and stop bit required. P : parity bit D 6 ~D 0 : data bit (ASCII) Clock : Timing signal. Note that requiring sync character (after a certain number of frames) to avoid losing synchronization. If two sync characters are used. it is called bi-sync. Data Clock D0 D1 D2 D3 D4 D5 D6 P D0 D1 D2 D3 D4 Po-Ning Chen@cm.nctu Background 37 Source of Information: (4) Computer Data Windows 98 Baud rate : 110 baud~ baud (different for different computers) (E)ven parity, (O)dd parity, (N)one-parity, Mark, Space 4~8 Data-bit 1, 1.5, 2 Stop-bit The name of mark and space for 1 and 0 comes from the days of telegraphy. Po-Ning Chen@cm.nctu Background 38

20 Source of Information: (4) Computer Data Po-Ning Background 39 Source of Information: (4) Computer Data Po-Ning Background 40

21 Source of Information: (4) Computer Data The computer data stream so formed is then applied to a device called a modem (modulatordemodulator). Unlike source traffic from speech or video, the computer data is often bursty rather than continuous. Po-Ning Chen@cm.nctu Background 41 Missed Part of Figure-1 in Text Source before entering the transmitter is often compressed (in order to save time or space). This part is missed in Figure 1 of the text. Po-Ning Chen@cm.nctu Background 42

22 With a source encoder, a digital communication system (rather an analog communication system) is formed. Po-Ning Chen@cm.nctu Background 43 Data Compression Lossless Data Compression (or Data Compaction) Completely reversible (or asymptotically reversible). E.g., Lempel-Ziv algorithm (PKZIP, compress, etc), which will be introduced in Chapter 9. Lossy Data Compression Non-reversible with loss of information in a controlled manner. E.g., JPEG, MPEG, etc. Po-Ning Chen@cm.nctu Background 44

23 Lossy Data Compression for Images JPEG (Joint Photographic Experts Group) An image coding standard Pixels are grouped in 8-by-8 block. DCT (discrete cosine transform) is then applied to each block. Quantize each of the 64 DCT coefficients according to a pre-specified table. Huffman-encode (introduced in Chapter 9) the quantization results. Po-Ning Chen@cm.nctu Background 45 Lossy Data Compression for Images DCT 1 F( u, v) = C( u) C( v) 4 1 f ( x, y) = u= 0 v= x= 0 y= 0 (2x + 1) uπ (2 y + 1) vπ f ( x, y)cos cos (2x + 1) uπ (2 y + 1) vπ C( u) C( v) F( u, v)cos cos where C( u) = 1, 2 1 for u = 0 otherwise Po-Ning Chen@cm.nctu Background 46

24 Lossy Data Compression for Video MPEG-1 (Motion Photographic Experts Group) video coding standard A video coding standard primarily for 30 fps (frames per second) video Result a bit-stream rate of 1.5 megabits per second Po-Ning Chen@cm.nctu Background 47 Lossy Data Compression for Video Design objective : To reduce four kinds of redundancies: Interframe (temporal) redundancy Its reduction is achieved through the use of prediction to estimate each frame from its neighbors. The resulting prediction error is transmitted for motion estimation and compensation. Interpixel redundancy within a frame Psychovisual redundancy Entropic coding redundancy Po-Ning Chen@cm.nctu Background 48

25 Lossy Data Compression for Video As with JPEG, the last three redundancies are reduced through the combined use of DCT, quantization and lossless entropic coding. Po-Ning Background 49 Lossy Data Compression for Audio MPEG-1 audio coding standard A perceptual (waveform) coder, as contrary to a vocoder The amplitude-time waveform of the decoded audio signal closely approximates that of the original audio signal. Po-Ning Chen@cm.nctu Background 50

26 Lossy Data Compression for Audio Encoding process Time-Frequency Mapping (sub-band decomposition) Psychoacoustic modeling (operates according to the psychoacoustic behavior of the human auditory system) Quantization and coding Frame-packing (format the quantized audio samples into a decodable bit stream) Po-Ning Chen@cm.nctu Background 51 Lossy Data Compression for Audio Why Psychoacoustic modeling? Human ears have a perceptual phenomenon known as auditory masking. Specifically, the human ear does not perceive quantization noise in a given frequency band if the average noise power lies below the masking threshold The masking threshold varies with frequency across the band. Hence, a perceptual weighting filter is applied to waveforms before quantization. Po-Ning Chen@cm.nctu Background 52

27 OSI (Open System Interconnection) model; the acronym DLC in the middle of the figure stands for data link control. OSI Po-Ning Background 53 Communication Networks OSI reference model was developed by ISO (International Organization for Standardization) in Figure 1 only concerns PHY layer. Now we take a quick look of its relation with higher layers, such as Network layers. Po-Ning Chen@cm.nctu Background 54

28 Communication Networks Network Layer : Routers Po-Ning Chen@cm.nctu Background 55 Communication Networks Routing mechanisms Circuit Switching Uninterrupted, exclusively use of links E.g., Telephone. Packet Switching Shared-on-demand links Po-Ning Chen@cm.nctu Background 56

29 Communication Networks Why OSI reference model? Each layer can perform its related subset of primitive functions without knowing the implementation details of the next lower layer. The adjacent layers communicate through welldefined interfaces, which defines the services offered by the lower layer to the upper layer. Po-Ning Background 57 Communication Networks The entities that comprise the corresponding layers on different systems are referred to as peer processes. Two peer entities then communicate through a well-defined set of rules of procedures, named Protocol. Again, this text/course primarily considers PHY layer. Po-Ning Chen@cm.nctu Background 58

30 Internet Internet A special communication network, as contrary to an Intranet. Features of Internet Applications are carried out independently of the technology employed to construct the network. The network technology is capable of evolving without affecting the applications. Po-Ning Chen@cm.nctu Background 59 Internet Architecture of Internet Cross-Router Data Exchange Direct Data Exchange Po-Ning Chen@cm.nctu Background 60

31 Internet Protocol (IP) Po-Ning Background 61 Internet Service Internet Service is Best Effort in nature. As a consequence, no guarantees of timely transmission, and even delivery. Po-Ning Chen@cm.nctu Background 62

32 Communication Channels Channels, where the noise/interference resides, can be roughly divided into two groups: Guided propagation channels E.g., telephone channels, coaxial cables, and optical fibers Free propagation channels E.g., broadcast channels, mobile radio channels, and satellite channels. Po-Ning Background 63 Communication Channels: (i) Telephone Channel Features of telephone channel A channel performs voice electrical signal sound Band-limited channel A speech signal (male or female) is essentially limited to a band from 300 to 3100 Hz. Po-Ning Chen@cm.nctu Background 64

33 Communication Channels: (i) Telephone Channel Measures used in characterizing channel Insertion loss = 10 log 10 (P 0 /P L ) P L = power delivered to a load from a source via the channel P 0 = power delivered to the same source not via the channel Channel P L P 0 Po-Ning Chen@cm.nctu Background 65 Communication Channels: (i) Telephone Channel Envelope delay The negative of the derivative of the phase response with respect to the angular frequency ω = 2πf. Example. Envelope delay = a for the next channel. g (t) j2πfa g( t a) H ( f ) = e The phase response of a channel filter H(f) is β(f), where H ( f ) = H ( f ) exp[ jβ ( f )]. Po-Ning Chen@cm.nctu Background 66

34 Communication Channels: (i) Telephone Channel Insertion Loss Envelope Delay Po-Ning Background 67 Communication Channels: (ii) Coaxial Cable A coaxial cable offers a greater degree of immunity to EMI, and a much higher bandwidth than twisted pair telephone lines. Example of its applications Local area network in an office environment. Cable television Po-Ning Chen@cm.nctu Background 68

35 Communication Channels: (iii) Optical Fiber Features Enormous potential bandwidth The bandwidth is roughly equal to 10% of the carrier frequency ( Hz). Notably, the transmission attainable limit (for additive white Gaussian noise with SNR=10dB) is around C = Blog (1 + SNR) 2 = ( = = )log ( dB /10 bit per second Gigabit per second ) Po-Ning Chen@cm.nctu Background 69 Communication Channels: (iii) Optical Fiber Low transmission loss 0.1dB/km Immunity to electromagnetic interference Small size and weight (thinner than human hair) Ruggedness and flexibility Possibility of being bent or twisted without damage. Po-Ning Chen@cm.nctu Background 70

36 Communication Channels: (iv) Wireless Broadcast Channels Transmission Up-convert the modulated baseband informationbearing signal to Radio Frequency (RF) passband signal Transmit the RF passband signal via antenna Reception Pick up the radiated waves by an antenna. Down-convert the received passband signal to baseband signal (perhaps through an intermediate step called the intermediate frequency (IF) band). Po-Ning Background 71 Communication Channels: (v) Mobile Radio Channels The main difference between this channel and the previous channel is the consideration of mobility. Due to mobility, there is no line-of-sight path for communication; rather, radio propagation takes place mainly by way of scattering from the surfaces of the surrounding buildings and by diffraction over and around them. This results in a multipath fading transmission. Po-Ning Chen@cm.nctu Background 72

37 Communication Channels: (v) Mobile Radio channels ( 1 α 1, τ ) s(t) Transmitter ( 2 α 2, τ ) Receiver α s( t τ ) 1 + α s( t τ ) 2 + α s( t τ ) 3 + n( t) ( 3 α 3, τ ) Notably, α j and τ j can also be functions of time. Po-Ning Chen@cm.nctu Background 73 Communication Channels: (vi) Satellite channels Satellite communications The satellite is placed in geostationary orbit. Geostationary orbit 1. The satellite orbits the Earth in exactly 24 hours (geosynchronous). 2. The satellite is placed in orbit directly above the equator on an eastward heading. It acts as a powerful repeater in the sky. It often uses 6 GHz for the uplink and 4 GHz for the downlink. Po-Ning Chen@cm.nctu Background 74

38 Communication Channels: (vi) Satellite channels The 6/4-GHz band offers the following attributes: 1. Relatively inexpensive microwave equipment. 2. Low attenuation due to rainfall Rainfall is a primary atmospheric cause of signal loss. 3. Insignificant sky background noise The sky background noise due to random noise emissions from galactic, solar and terrestrial sources reaches its lowest level between 1 and 10 GHz. Po-Ning Chen@cm.nctu Background 75 Communication Channels: (vi) Satellite channels A typical satellite in the 6/4-GHz band is assigned a 500 MHz bandwidth, which is divided among 12 transponders. Each transponder can carry at least one color television signal, 1200 voice circuits, or digital data at a rate of 50 Mb/s. Po-Ning Chen@cm.nctu Background 76

39 Classifications of Communication Channels (according to the natures or resources) Linear or non-linear A wireless radio channel is linear whereas a satellite channel is usually non-linear Time invariant or time varying An optical fiber is time invariant, whereas a mobile radio channel is typically time varying. Band limited or power limited A telephone channel is band limited, whereas an optical fiber link and a satellite channel are both power limited. Po-Ning Chen@cm.nctu Background 77 Classification of Modulation Process Continuous-wave modulation A sinusoidal wave is used as the carrier. It can be further classified as: Amplitude modulation (AM) : Amplitude of the carrier is varied in accordance with the message. Frequency modulation (FM) : Frequency of the carrier is varied in accordance with the message. Phase modulation (PM) : Phase of the carrier is varied in accordance with the message. Po-Ning Chen@cm.nctu Background 78

40 Classification of Modulation Process Pulse modulation. The carrier consists of a sequence of rectangular pulses. It can be sub-divided to: Analog pulse modulation Digital pulse modulation Po-Ning Chen@cm.nctu Background 79 Classification of Modulation Process Analog pulse modulation Pulse-amplitude modulation (PAM), pulse-duration modulation (PDM), pulse-position modulation (PPM) The amplitude, duration, position of the pulses varies in accordance with the message signals. Digital pulse modulation Pulse-code modulation (PCM) Po-Ning Chen@cm.nctu Background 80

41 Example of PAM (telephone system) Sampling the voice according to some clocks. Po-Ning Background 81 Example of PCM Originate from PAM, but with the following modifications. Convert the (sampled) pulse into bits, e.g., 8 bits. All 8 bits of the input PCM signal are gated to the output port in parallel. The gate can now be designed using truth table which facilitates system integration or multiplexing. Po-Ning Chen@cm.nctu Background 82

42 What is multiplexing? To combine (several modulated) signals for their simultaneous (or concurrent) transmission. Frequency-division multiplexing (FDM) Time-division multiplexing (TDM) Code-division multiplexing (CDM) Wavelength-division multiplexing (WDM), specifically for use of optical fibers. Some treats WDM as a special case of FDM, since c = f λ. Po-Ning Chen@cm.nctu Background 83 Shannon s Information Capacity Theorem The underlying limit for digital communications Po-Ning Chen@cm.nctu Background 84

43 Transmission Rate = Source code bit per second (Information bit per second) Po-Ning Chen@cm.nctu Background 85 Shannon s Information Capacity Theorem Reliable transmission rate (for pre-specified modulator, channel and demodulator). The rate for which a proper design of channel encoder-decode pair can fulfill arbitrarily small error requirement. Shannon finds the general formula for the largest reliable transmission rate, which he baptized as (coding) channel capacity. Po-Ning Chen@cm.nctu Background 86

44 Shannon s Information Capacity Theorem For additive white Gaussian noise as demodulator input = modulator output + Gaussian the channel capacity is equal to C = B log 2 (1+SNR) bit/second, where B is the bandwidth. It took 45 years (1948~1993) of research to reach this capacity! Po-Ning Chen@cm.nctu Background 87 An Exemplified Ideal Digital Communication Problem Phase Shift Keying Channel Encoder 0110 Modulator, m(t), m(t), m(t), m(t) m(t) No IF here because this is an ideal system > < 0 y T T dt 0 T Local carrier cos(2πf c t) x(t) w(t) Carrier wave A c cos(2πf c t) s(t) correlator Po-Ning Chen@cm.nctu Background 88

45 An Exemplified Ideal Digital Communication Problem Phase Shift Keying Assume that the local carrier (at the receiver end) is exactly the same as the transmitter carrier. Assume that the correlator is completely synchronized with the transmitter. So the integration inside correlator covers a complete message signal m(t). (In other words, it won t happen that the integration inside correlator covers 80% of the current m(t), but 20% of the previous m(t).) Po-Ning Chen@cm.nctu Background 89 y T = = = 0 T 0 T 0 = ± A = ± A x( t)cos(2πf t) dt [ s( t) + w( t)]cos(2πf t) dt T [ ± A cos(2πf t) + w( t)]cos(2πf t) dt c c c 0 T 0 T 1 = ± AcT m 2 1 = ± AcT + 2 T 0 c c 2 cos (2πf t) dt + c c 0 1 cos(4πf ct) dt T Ac c 2 0 T 0 cos(4πf t) dt + w( t)cos(2πf t) dt c T c w( t)cos(2πf t) dt w( t)cos(2πf t) dt 0 T c c w( t)cos(2πf t) dt (By assuming that f c is a multiple of 1/T.) c Po-Ning Chen@cm.nctu Background 90

46 An Exemplified Ideal Digital Communication Problem Phase Shift Keying Some interesting issues to consider. What if the local carrier does not equal the transmitter carrier. y T [ ± Ac cos(2πf rct) + w( t)]cos(2πf t) dt 0 = T tc What if f c is not a multiple of 1/T. What if the receiver does not synchronize with the transmitter? What is the BER of this system? Po-Ning Chen@cm.nctu Background 91 An Exemplified Ideal Digital Communication Problem Phase Shift Keying Is the correlator receiver optimal in the sense of BER? Is the sign-decision optimal in the sense of BER? Is the above combination optimal in the sense of BER? Is the BER robust for imperfect system, such as timing and carrier mismatch? Is the rectangular m(t) a fine choice? Moreover, is PSK a fine choice? If affirmative, in what sense?. Po-Ning Chen@cm.nctu Background 92

47 An Exemplified Ideal Digital Communication Problem Phase Shift Keying All these problems will be hopefully answered in this course (and subsequent courses). Po-Ning Background 93