The Comparison Of Maximum-Likelihood and MAP Decoding Techniques

Student: Ng Cheark Yeong

Supervisor: John Homer

Category: Engineering Thesis Project - Communications

The demand for efficient and reliable digital data transmission is increasing, particularly over long-range communication links, making error-correcting techniques more essential in communication.

In the presence of noise, the capacity of the communication channel decreases as a result of the errors made in transmission. This thesis examines the theory behind coding and the performance of error control coding with the comparison of two decoding techniques. They are the Maximum-Likelihood (ML) and Maximum-a-posteriori (MAP) decoding.

ML decoding decides the encoded sequence that has the minimum distance from the received sequence. However, the MAP decoding takes into account the a-prior information and is therefore generally more superior to the ML decoding.

A Matlab software program is used to observe the performance of these two decoding techniques. It has been observed that the MAP decoding has a much more superior performance under low Eb/No and high bit error rate.

Thesis Document (PDF)

Poster Presentation (PDF)