New error-detection (2)
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This document discusses various techniques for error detection and correction in digital communications. It begins by describing common types of errors like single-bit and burst errors. It then explains error detection methods like parity checks and cyclic redundancy checks (CRCs). CRCs use cyclic codes and polynomial division to detect errors. Block codes like Hamming codes can detect and correct errors by ensuring a minimum Hamming distance between codewords. Checksums are also discussed as a simpler error detection technique than CRCs. The document provides examples to illustrate how these different error control methods work.
New error-detection (2)
- 1. Error Detection and Correction 1. Introduction 2. Block Coding 3. Linear Block Codes 4. Cyclic Codes 5. Checksum
- 2. Type of Errors • An electromagnetic signal is subject to interference from heat, magnetism, and other forms of electricity • Single-bit error: 0 ® 1 or 1 ® 0 • Burst error: 2 or more bits have changed
- 3. Single-Bit Error • Only one bit of a given data unit is changed • The least likely type of error in serial transmission • Single-bit error can happen in parallel transmission
- 4. Burst Error • Two or more bits in the data unit have changed • Burst error does not necessarily mean that the errors occur in consecutive bits • Most likely to happen in a serial transmission • Number of bits affected depends on the data rate and duration of noise
- 5. Redundancy • Error detection uses the concept of redundancy, which means adding extra (redundant) bits for detecting errors at the destination
- 6. Error Control • Detection Versus Correction – Detection: error ? yes or no – Correction: Need to know the exact number of bits that are corrupted, and their location in the message • Forward Error Correction Versus Retransmission – Retransmission (resending) : Backward error correction • Coding for redundancy – Block coding: discussed in our textbook – Convolution coding
- 7. Modular Arithmetic • In modulo-N arithmetic, we use only the integers in the range 0 to N- 1, inclusive. • Adding: 0 + 0 = 0 0 + 1 = 1 1 + 0 = 1 1 + 1 = 0 • Subtracting: 0 – 0 = 0 0 – 1 = 1 1 – 0 = 1 1 – 1 = 0 • XORing of two single bits or two words
- 8. Block Coding • Divide the message iinnttoo bblloocckkss,, eeaacchh ooff kk bbiittss,, ccaalllleedd ddaattaawwoorrddss.. • AAdddd rr rreedduunnddaanntt bbiittss ttoo eeaacchh bblloocckk ttoo mmaakkee tthhee lleennggtthh nn == kk ++ rr.. TThhee rreessuullttiinngg nn--bbiitt bblloocckkss aarree ccaalllleedd ccooddeewwoorrddss • EExxaammppllee:: 4B/5B block coding – k = 4 and n = 5. – 2k = 16 datawords and 2n = 32 codewords.
- 9. Error Detection in Block Coding • Example: Assume that k = 2 and n = 3 (Table 10.1)
- 10. Error Detection: Example • Assume the sender encodes the dataword 01 as 011 and sends it to the receiver. Consider the following cases: 1. The receiver receives 011 which is a valid codeword. The receiver extracts the dataword 01 from it. 2. The codeword is corrupted during transmission, and 111 is received. This is not a valid codeword and is discarded. 3. The codeword is corrupted during transmission, and 000 is received. This is a valid codeword. The receiver incorrectly extracts the dataword 00. Two corrupted bits have made the error undetectable. An error-detecting code can detect only the types of errors for which it is designed; other types of errors may remain undetected
- 11. Error Correction in Block Coding • Example: Assume that k = 2 and r = 3 n = 5
- 12. Error Correction: Example • Assume the dataword is 01. The sender creates the codeword 01011. The codeword is corrupted during transmission, and 01001 is received. First, the receiver finds that the received codeword is not in the table. This means an error has occurred. The receiver, assuming that there is only 1 bit corrupted, uses the following strategy to guess the correct dataword 1. Comparing the received codeword with the first codeword in the table (01001 versus 00000), the receiver decides that the first codeword is not the one that was sent because there are two different bits. (the same for third or fourth one in the table) 2.. The original codeword must be the second one in the table because this is the only one that differs from the received codeword by 1 bit.
- 13. Hamming Distance • The Hamming distance between two words is the number of differences between corresponding bits. • Example: Hamming distance d(10101, 11110) is 3 • The minimum Hamming distance is the smallest Hamming distance between all possible pairs in a set of words • Example for Table 10.1 - dmin = 2
- 14. Hamming Distance • Three parameters to define the coding schemes – Codeword size n – Dataword size k – The minimum Hamming distance dmin • Coding scheme C(n, k) with a separate expression for dmin • Hamming distance and error – Hamming distance between the received codeword and the sent codeword is the number of bits that are corrupted • Minimum distance for error detection – To guarantee the detection of up to s errors in all cases, the minimum Hamming distance in a block code must be dmin = s + 1.
- 15. Minimum Hamming Distance: Example • The minimum Hamming distance in Table 10.1 is 2. This code guarantees detection of only a single error. For example, if the third codeword (101) is sent and one error occurs, the received codeword does not match any valid codeword. If two errors occur, however, the received codeword may match a valid codeword and the errors are not detected. • In Table 10.2, it has dmin = 3. This code can detect up to two errors. When any of the valid codewords is sent, two errors create a codeword which is not in the table of valid codewords. The receiver cannot be fooled. However, some combinations of three errors change a valid codeword to another valid codeword. The receiver accepts the received codeword and the errors are undetected.
- 16. To guarantee the detection of up to s errors in all cases, minimum Hamming distance in a block code must be dmin = s + 1. To guarantee correction of up to t errors in all cases, the minimum Hamming distance in a block code must be dmin = 2t + 1.
- 17. Linear Block Codes • Almost all block codes used today belong to a subset called linear block codes. • A linear block code is a code in which the exclusive OR (addition modulo-2) of two valid codewords creates another valid codeword • The minimum Hamming distance is the number of 1s in the nonzero valid codeword with the smallest number of 1s
- 18. Linear Block Code: Parity-Check Code • A simple parity-check code is a single-bit error-detecting code in which n = k + 1 with dmin = 2. The extra bit called parity bit is selected to make the number of 1s in the codeword even.
- 19. K=4, n=5 The addition of the 4 bits of the data word is the parity bit (modulo 2 ). If the no. of 1s are even, the result is 0; if the no. of 1s are odd the result is 1.
- 20. Encoder and Decoder for Parity-Check Code • The result of addition oovveerr aallll 55 bbiittss:: ssyynnddrroommee If the syndrome is 0, there is no error in the codeword, the data portion of the codeword (dataword) is accepted.
- 21. Assume the sender sends 1011, codeword is 10111, consider 1. Syndrome 0, no error and dataword 1011 is created. 2. One bit a1 changes, Syndrome 1, No dataword is created. 3. One bit r0 changes, Syndrome 1, No dataword is created. 4. An error with r0 and a3. Codeword is 00110, Syndrome is 0, wrong dataword 0011 is accepted. So parity check detector can not detect even no. of errors. 5. Three bits a1, a2 and a3 are changed. Codeword is 01011. Syndrome is 1. Dataword not created. parity check guaranteed to detect one single error, can also find odd number of errors.
- 22. 2 Dimensional Parity-Check Code
- 23. 2 Dimensional Parity-Check Code
- 24. Linear Block Code: Hamming Code • All Hamming codes discussed in textbooks have dmin = 3. • Dataword (k bits), codeword (n bits), choose m >=3 as the relationship between m and n in these codes is n = 2m − 1 and k=n-m, r = m. If m=3, then n=7 and k=4, thus C(7,4) with dmin = 3
- 25. Encoder and Decoder for Hamming Code
- 26. Hamming Code • rr00 == aa22 ++ aa11 ++ aa00 mmoodduulloo--22 • rr11 == aa33 ++ aa22 ++ aa11 mmoodduulloo--22 • rr22 == aa11 ++ aa00 ++ aa33 mmoodduulloo--22 • ss00 == bb22 ++ bb11 ++ bb00 ++ qq00 mmoodduulloo--22 • ss11 == bb33 ++ bb22 ++ bb11 ++ qq11 mmoodduulloo--22 • ss22 == bb11 ++ bb00 ++ bb33 ++ qq22 mmoodduulloo--22
- 27. Logical Decision by Decoder • Let us trace the path of three datawords from the sender to the destination: 1 The dataword 0100 becomes the codeword 0100011. The codeword 0100011 is received. The syndrome is 000, the final dataword is 0100. 2. The dataword 0111 becomes the codeword 0111001. The codeword 0011001 received. The syndrome is 011. After flipping b2 (changing the 1 to 0), the final dataword is 0111. 3. The dataword 1101 becomes the codeword 1101000. The codeword 0001000 received (two errors). The syndrome is 101. After flipping b0, we get 0000, the wrong dataword. This shows that our code cannot correct two errors.
- 28. Burst Error Correction Using Hamming Code
- 29. Cyclic Code: CRC • Cyclic codes are special linear block codes with oonnee eexxttrraa pprrooppeerrttyy.. • IIff aa ccooddeewwoorrdd iiss ccyycclliiccaallllyy sshhiifftteedd ((rroottaatteedd)),, tthhee rreessuulltt iiss aannootthheerr ccooddeewwoorrdd • Cyclic Redundancy Check (CRC)
- 30. CRC Encoder and Decoder
- 31. Division in CRC Encoder
- 32. Division in CRC Decoder
- 33. Polynomials • Degree of a polynomial: the highest power in the polynomial Example: x6 + x + 1 the degree ‘6’
- 34. CRC Division Using Polynomials • The divisor in a cyclic code is normally called the generator polynomial or simply the generator.
- 35. Error Detection • Single-bit error If the generator has more than one term and the coefficient of x0 is 1, all single errors can be caught. • Two isolated single-bit error If a generator cannot divide xt + 1 (t between 0 and n – 1), then all isolated double errors can be detected
- 36. Summary and Standard Polynomials • A good polynomial generator needs to have the following characteristics: 1. It should have at least two terms. 2. The coefficient of the term x0 should be 1. 3. It should not divide xt + 1, for t between 2 and n − 1. 4. It should have the factor x + 1.
- 37. Checksum • Tendency is to replace the checksum with a CRC • Not as strong as CRC in error-checking capability • One’s complement arithmetic – We can represent unsigned numbers between 0 and 2n – 1 using only n bits – If the number has more than n bits, the extra leftmost bits need to be added to the n rightmost bits (wrapping) – A negative number can be represented by inverting all bits. It is the same as subtracting the number from 2n – 1
- 38. Checksum: Example • The sender initializes the checksum to 0 and adds all data items and the checksum. However, 36 cannot be expressed in 4 bits. The extra two bits are wrapped and added with the sum to create the wrapped sum value 6. The sum is then complemented, resulting in the checksum value 9 (15 − 6 = 9).
- 39. Internet Checksum Sender site: 1. The message is divided into 16-bit words. 2. The value of the checksum word is set to 0. 3. All words including the checksum are added using one’s complement addition. 4. The sum is complemented and becomes the checksum. 5. The checksum is sent with the data. Receiver site: 1. The message (including checksum) is divided into 16-bit words. 2. All words are added using one’s complement addition. 3. The sum is complemented and becomes the new checksum. 4. If the value of checksum is 0, the message is accepted; otherwise, it is rejected.