Data Communication

Data Communication and Ema sonv il: Networ q@hcmut.edu king Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT Cont  Chapter 1: Medium of ent PHY Layer RS4 Wired and Wireless Media Physical layer standards: RS232, RS422, Line Coding Digital modulation/demodulation Channel parameters Gaussian noise and BER 85  Chapter 2: Data Transmission Asynchronous transmission Telecomm Synchronous transmission Dept Faculty of Channel Coding EEE DCN‐ 2013 HCM UT Coding  EBCDIC (Extended Binary Coded Decimal Interchange schemes Code):  Invented by IBM  8‐bit character encoding used mainly on IBM mainframe and IBM midrange computer operating systems  ASCII (American Standards Committee for Information Interchange): defined by ITU‐T  character‐encoding scheme originally based on the English alphabet that encodes 128 specified characters ‐ the numbers 0‐ Telecomm DCN‐ 9, the letters a‐z and A‐Z, some basic Dept Faculty of EEE 2013 HCM UT ble  Data characters  Control characters Telecomm Dept Faculty of EEE EBCDIC Ta DCN‐ 2013 HCM UT  Data  Cont charac ble characters rol ASCII Ta ters Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT  ASCII unprintable characters: ble Telecomm Dept Faculty of EEE ASCII Ta DCN‐ 2013 HCM UT Bu pology Network To  Point‐to point St ar  Multip oint Rin g  Me sh  s   Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT  Communication Simplex communication is  permanent uni‐ directional communication (e.g Radio, TV)  types Half duplex: A half duplex link can communicate in only one direction, at a time Two way communication is possible, but not simultaneously E.g talk‐ back radio, Citizen Bands radio Telecomm Full duplex communication is Dept two‐way communication Faculty of achieved over a physical link that EEE DCN‐ 2013 HCM UT Transmission The transmission of binary data across a link can be modes  accomplished in either parallel or serial mode In asynchro parallel synchronan isochron transmis mode, are sent dwith each sion: multiple nous, bitsous, ous clock tick In serial mode, bit is sent with each clock tick While there is only one way to send parallel data, there are three Telecomm DCN‐ subclasses of serial Dept 2013 Faculty of EEE HCM UT Parallel Bits are transmitted sa tim High in busspeed at the dista me e transmission over short nce    Example: PC‐printer Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT Sources of  Redundancy Compressibility Recognize repeating patterns Exploit using • Dictionary • Variable length encoding  Human perception Less sensitive to some information Can les import da discard s ant Telecomm Dept Faculty of EEE ta DCN‐ 2013 HCM UT Data Packed Decimal: A packed decimal representation stores two Compression  decimal digits in one byte For example,  the value 23 would be stored in two nibbles, using the  hexadecimal digits and (the bit representation would be 0010 and the o thi charac Exam AAAAABB = 0011) Relative coding: finstead of transmitting whole number number s ter ple: theBBCC value, the transmitter only transmits the difference between A5B4C2 Telecomm DCN‐ values Dept Faculty of Character EEE Suppression: when transmitting the same 2013 HCM UT  What is  difference in this tabl e?  Why Wha the basic the thi tabl length t is principle of s e? to letter A, E is build shorte r than Telecomm the Dept Faculty of length EEE Huffman DCN‐ 2013 HCM UT Huffman Huffman coding is statistical coding technique code   Approach   Variable length encoding of symbols  Exploit statistical frequency of symbols  Efficient when symbol probabilities vary widely Principle  Use fewer bits to represent frequent symbols  Use more bits to represent infrequent symbolsA A A Telecomm Dept Faculty of EEE A B B A A DCN‐ 2013 HCM UT Huffman Code  siz Example Expecte e d Symbol A B C D Frequency 13% 25% 50% 12% Original Encoding 00 01 10 11 Huffman Encoding bits bits bits bits 110 10 bits bits 111 bit bits  ⇒ 1/8×2 + 1/4×2 + 1/2×2 +  Huffman ⇒=1/8×3 + 1/4×2 + 1/2×1 + Origin 1/8×2 bits/symbol 1/8×3 Telecomm = 1.75 bits/symbol al Dept Faculty of EEE DCN‐ 2013 HCM UT 6 Huffman coding  Encoding Calculate frequency of encod principle symbols ing Create binary tree representing “best” Sym Stag Stag Stag Stag Codew Use binary tree to 0 bol e1 e2 e3 e ord encode symbols S0 0.4 00 0.2symbol,0.2 0.4 For each output path S2 0.2 0.2 0.2 from root to leaf S3 0.1 • Size of encoding =0.2length of Telecomm S4 0.1 path Dept S1 • Faculty of Save binary tree EEE 0.4 10 11 010 DCN‐ 011 2013 HCM UT Huffman coding  Decoding tre principle Read compressed file & binary Use binary tree decode Follow frotoro t lefile path  Example: Encoder Telecomm Dept Faculty of EEE m ot o af e Deco der DCN‐ 2013 HCM UT Performance  Entropy: (1/p ) (bits/sy Evaluation H=∑pi log2  Average N =length pi i of codewords:  Variance: ∑ Ni measure what? mbol) (bits/sy mbol) σ2=∑pi (Ni‐ N)2  of encodi Efficiency Bit rate codeword set: R i th sym rat (symb (after ng): Telecomm DCN‐ h = H/N S Dept.Rb= RS.N 2013 s e bol e ol/s) (bps), Faculty of HCM EEE UT Huffman Code  Prefix code Properties No code is a prefix of another code • 00 Example: // not legal Huffman(“ 001 Can as complete code I”) stop as soonprefix • Huffman(“X”) code found No need for end‐of‐code marker  Nondeterministic If tw tre wit sa mini Multipletha Huffman coding possible for sameweig input more n o es h me mal ht Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT Run‐Length Run‐length encoding is probably the simplest method of compression It coding can be used to compress data made of any    combination of symbols It does not need to know the frequency of occurrence of symbols and can be very efficient if data is represented as 0s and 1s The general idea behind this method is to replace consecutive repeating occurrences of a symbol by one occurrence of the symbol followed by the Telecomm of occurrences DCN‐ number Dept 2013 Faculty of HCM The method can be even more efficient if the EEE UT  Run‐Length Used in Black‐  White Facsimile coding Page is divided into:  Height: 3.85‐7.7 lines/mm   Width: 8.05 (pels/mm) Each page abo unencoded contains ut Fax 2Mb Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT  Run‐Length Each line in a page will have a  number of black/white pixel continuous sequence  Each continuous bit sequence is  End of pa encoded by wi b end wit  Termination each ge ll code: e edin the h Telecomm 6range EOL 63 coding switches between black Dept Faculty of EEE DCN‐ 2013 HCM UT Run‐Length  Example 1: line with w, b, 200 coding w, b, EOL! 0111 011 010111 10011 10 00000000001  Exampl e 2: What is the transmitted bit stream? Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT Lempel Ziv Lempel Ziv (LZ) encoding is an example of a category of encoding  algorithms called dictionary‐based encoding idea is to by their strings canThe be substituted t redu th amo o informa transmit create a dictionary (a table) of strings o index in the dictionary ce unt the f tion ted used eduring communication session If both the sender and the receiver have a copy of the dictionary, then Telecomm DCN‐ previously‐encountered Dept 2013 Faculty of EEE HCM UT Lossy Compression  JPEG (Joint Photographic  MPEGGroup) (Moving Gro Methods Experts  (MP aud lay Picture Experts MP3 EG io er ) Telecomm Dept Faculty of EEE up) DCN‐ 2013 HCM UT ... Me sh  s   Telecomm Dept Faculty of EEE DCN‐ 2013 HCM UT  Communication Simplex communication is  permanent uni‐ directional communication (e.g Radio, TV)  types Half duplex: A half duplex... direction, at a time Two way communication is possible, but not simultaneously E.g talk‐ back radio, Citizen Bands radio Telecomm Full duplex communication is Dept two‐way communication Faculty of