1. Hamming Code Rachel Ah Chuen

2. Basic concepts Networks must be able to transfer data from one device to another with complete accuracy. Data can be corrupted during transmission. For reliable communication, errors must be detected and corrected.

3. Types of Errors

4. Single - bit error

5.  Single bit errors are the least likely type of errors in serial data transmission because the noise must have a very short duration which is very rare.  However this kind of errors can happen in parallel transmission. Single-bit error

6. Burst error

7.  The term burst error means that two or more bits in the data unit have changed from 1 to 0 or from 0 to 1.  Burst errors does not necessarily mean that the errors occur in consecutive bits.  The length of the burst is measured from the first corrupted bit to the last corrupted bit. Burst error

8. Hamming Code  In the late 1940 ’ s Richard Hamming recognized that the further evolution of computers required greater reliability, in particular the ability to not only detect errors, but correct them.  His search for error-correcting codes led to the Hamming Codes, and the extended Hamming Codes, 1-error correcting and 2-error detecting codes.

9. Definitions  For linear codes, encoding is a linear transformation c that maps a message m to a codeword c(m).  Block codes means all codewords c(m) have the same length, which we denote as n.  Let k be the length of information bits that we encode. Then there are n-k redundancy bits in each codeword, called parity check bits, which are left for error correction.  (n, k) specify the parameters (codeword length and parity check bit length) for a block code.

10. Hamming Distance  The Hamming distance, d_H is the number of bits that have to be changed to get from one bit pattern to another.  Example: c1=(10010101) & c2=(10011001) have a hamming distance of 2  What about c1 = (101101) and c2 = (100110)?

11. Minimum Hamming Distance  Let d to be the minimum Hamming distance between any two distinct codewords of a code C as  A code with minimum distance d between codewords can detect d-1 errors and can correct (d-1)/2 errors.

12. Hamming weight  w(S) defined as the sum of its non-zero entries  A linear code is completely defined by all the codewords for messages of weight 1.

13. Hamming Code  The Hamming code is a single error correction linear block code with (n, k) = (2 m -1, 2 m -1-m)  where m = n k is the number of check bits in the codeword.  The simplest non-trivial code is for m = 3, which is the (7,4) Hamming code.  Generator matrix  Where S is k x (n k)

14. Hamming code  Suppose our matrix G generates a single error correcting code. Then there are no code words of weight 1 or 2, and the parity check portion S of G must satisfy the following 2 conditions:

15. (7,4) Hamming Code

16.  For every generator matrix g=[ I S], there is a parity check matrix H defined by

17. Example  received string r = (1110111)

18. Parity Errors  The class of Hamming single error correcting codes is noteworthy because they are particularly efficient in the use of parity bits.  The (7,4) Hamming code uses 3 parity bits to protect 4 data bits;

19. (15,11) code

20. Parity Computation  (7,4) code  Computations by receiver  Steps

21. Combination of syndrome bits  Appropriate corrective action for each combination of the syndrome bits