linear block code

15
LINEAR BLOCK CODING Presented by: Manish Srivastava

Upload: manish-srivastava

Post on 02-Jun-2015

5.148 views

Category:

Documents


2 download

TRANSCRIPT

Page 1: Linear block code

LINEAR BLOCK CODING

Presented by:

Manish Srivastava

Page 2: Linear block code

LINEAR BLOCK CODE

In a (n,k) linear block code: 1st portion of k bits is always identical to the

message sequence to be transmitted.

2nd portion of (n-k ) bits are computed from message bits according to the encoding rule and is called parity bits.

Page 3: Linear block code

SYNDROME DECODING

The generator matrix G is used in the encoding operation at the transmitter

The parity- check matrix H is used in the decoding operation at the receiver

Let , y denote 1-by-n received vector that results from sending the code x over a noisy channel

y=x +e

Page 4: Linear block code

For i=1,2,….., n ei= 1,if an error has occurred in the ith

location 0 ,otherwise o s=yHt

Page 5: Linear block code

PROPERTIES

Property 1: The syndrome depends only on the

error pattern and not on the transmitted code

word. S=(x+e)Ht

=xHt+ eHt

=eHt

Page 6: Linear block code

PROPERTY 2:

All error pattern that differs at most by a code word have the same syndrome.

For k message bits ,there are 2k distinct codes denoted as xi ,i=0,1, ………. 2k -1

we define 2k distinct vectors as e =e+ xi i=0,1,…….. 2k-1

Page 7: Linear block code

=e + =e

Page 8: Linear block code

PROPERTY 3: The syndrome s is the sum of those

columns of matrix H corresponding to the error locations

H=[ , ………., ] therefore, s=

Page 9: Linear block code

PROPERTY 4:

With syndrome decoding ,an (n,k) linear block code can correct up to t errors per code word ,provided that n and k satisfy the hamming bound

≥ ( ) where ( ) is a binomial

coefficient ,namely ( )= n!/(n-i)!i!

Page 10: Linear block code

MINIMUM DISTANCE CONSIDERATIONS:

Consider a pair of code vectors x and y that have the same number of elements

Hamming distance d(x,y): It is defined as the number of locations in which their respective elements differ .

Hamming weight w(x) : It is defined as the number of elements in the code vector.

Page 11: Linear block code

Minimum distance dmin: It is defined as the smallest hamming distance between any pair of code vectors in the code or smallest hamming weight of the non zero code vectors in the code .

Page 12: Linear block code

An (n,k) linear block code has the power to correct all error patterns of weight t or less if ,and only if

d( ) ≤2t+1 An (n,k) linear block code of minimum distance dmin

can correct upto 1 error if and only if

t≤ [1/2 (dmin – 1)].

Page 13: Linear block code

Easiest to detect and correct errors.

Extra parity bit does not convey any information but detects and corrects errors.

Transmission bandwidth is more.

Extra bit reduces the bit rate of transmitter and also its power.

Advantages Disadvantages

Page 14: Linear block code

APPLICATIONS

Used for error control coding. Storage-magnetic and optical data storage in

hard disks and magnetic tapes and single error correcting and double error correcting code(SEC-DEC) used to improve semiconductor memories.

Communication-satellite and deep space communications.

Page 15: Linear block code

THANK YOU!!