Research Abstracts Online
January 2009 - March 2010
University of Minnesota Twin Cities
Institute of Technology
Department of Electrical and Computer Engineering
PI: Jaekyun Moon
Iterative Detection and Channel Estimation Algorithm Development for Heavy Interference Channels
The goal of this project is to evaluate the performance of new coding systems developed for magnetic and tape recording applications. The industry standard frame error rates for such applications is in the order of 1E-13, which means an average of 1E15 frames have to be simulated in order to obtain results with acceptable accuracy. The processing of each frame involves a Monte Carlo simulation of data encoding, symbol mapping, channel write, channel read, channel detection, and data decoding. Furthermore, due to the independence between processed frames, the simulation can be distributed among as many as possible independent processing units, and the final results of all units averaged to obtain the final estimate of the performance metric, whether it is bit or frame error rate.
These researchers have developed thoroughly tested channel models and encoder-decoder simulators for their codes and it is essential to investigate their performance advantages for online high fidelity operation. The stringent performance requirement is due to the nature of recording read errors, in which delay-requirements and unrecoverable media and head defects make head rereads ineffective. As such, robust codes that are resilient to the worst-case error environment are designed and tested by Monte Carlo simulation. The researchers design the codes with the turbo coding concept for soft iterative decoding of low-density parity check codes and joint channel detection and code decoding for inter-symbol interference equalization.
Hakim Alhussien, Graduate Student
Seongwook Jeong, Graduate Student
Jaewook Lee, Graduate Student
Daejung Yoon, Graduate Student