100408-lecture16

# 100408-lecture16 - 1 EE522 Communications Theory Spring 2010 Instructor Hwang Soo Lee Lecture#16 – Block Codes Performance Evaluation and

This preview shows pages 1–10. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 1 EE522 Communications Theory Spring 2010 Instructor: Hwang Soo Lee Lecture #16 – Block Codes: Performance Evaluation and Tradeoffs 2 Announcements ¡ Handout: Lecture #16 Notes 3 Error Correction Codes ¡ Names: ¢ Error Correction Coding ¢ Channel Coding ¢ Forward Error Correction ¡ Channel coding provides a practical way to achieve performance which more nearly approaches theoretical capacity. ¡ Channel coding trades bandwidth efficiency for energy efficiency. 4 Encoding and Decoding of Error Correction Codes ¡ Encoding operation usually easy ¢ can be thought of in terms of parity checks. ¡ Decoding operation is usually complex. ¡ Many good practical codes have been developed for use in communication systems. We focus on block codes first. 5 Terminology for Block Codes ¡ k = number of input symbols (usually bits). ¡ n = number of output symbols (usually bits). ¡ is the code rate. ¡ is the minimum distance. ¡ is the error correcting capability. ¡ Codes can be classified as linear, systematic, and cyclic. 6 Encoding of Block Codes ¡ Encoding can be viewed in terms of adding parity bits to the information bits. ¡ This operation can be described in terms of matrix multiplication: where = vector of k input data bits = codeword of n output data bits = k x n Generator Matrix ¡ Only required kn multiplies and additions. 7 The Generator Matrix G ¡ Let the message bits by a vector ¡ Then any linear code can be represented by a Generator Matrix ¡ The row vectors g-form a linearly independent basis for the code C 8 Encoding with a Generator Matrix ¡ The transmitted codeword is generated by the equation ¢ C=mG , where ¢ m is a k element row vector ¢ c is an n element row vector ¢ note that c can be expressed as a linear combination of row vectors 9 Systematic Representation of...
View Full Document

## This note was uploaded on 11/23/2010 for the course EE EE522 taught by Professor Eeehwangsoo during the Spring '10 term at Korea Advanced Institute of Science and Technology.

### Page1 / 27

100408-lecture16 - 1 EE522 Communications Theory Spring 2010 Instructor Hwang Soo Lee Lecture#16 – Block Codes Performance Evaluation and

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online