Saeed Sharifi Tehrani

Saeed Sharifi Tehrani

University of California, San Diego

California

PhD student Saeed Sharifi Tehrani has been working closely with Prof. Paul H. Siegel at the University of California, San Diego (UCSD) in the Center for Magnetic Recording Research (CMRR). The CMRR is an internationally renowned research center founded in 1983 by a consortium of U.S. companies in the magnetic recording industry. The Center is located in a 26700 square foot building on the UCSD campus. CMRR researchers and affiliated faculty members working in areas such as physics, electrical and computer engineering, computer science and engineering, mechanical and aerospace engineering, and operations management lead an innovative, interdisciplinary research program to develop significant advances in ultra-high density storage and ultra-high data rates, particularly for disk and tape recording systems. The CMRR has been active in different aspects of digital storage systems, magnetic recording, signal processing and information theory. In particular, novel error correcting methods for storage systems have been the center of great attention in CMRR.

Mr. Sharifi Tehrani’s internship research project aims to link stochastic decoding, as a new decoding approach, with the application of error control coding for high-density storage systems. Recently, there has been great attention at both university and industry R&D levels to use Low Density Parity Check (LDPC) codes for media storage systems. A promising LDPC coding solution for storage technology must not only achieve very low bit-error-rate error-correcting performance, but also must be suitable for high speed VLSI implementation to meet the high data rate requirements. The stochastic decoding approach has appealing features and high potential in this respect because it has low hardware complexity, it can provide high throughput, and it has been shown that it can provide promising decoding performance. However, the channel models used in data storage systems are technology-dependant and have different characteristics compared to the channel models usually considered for wireline or wireless communications. Therefore, the focus of this internship has been on investigating the application of stochastic LDPC decoding approach for partial response channel models used in storage systems. The internship explores this at both the decoding algorithm and the hardware implementation levels.

This internship provides a unique opportunity for the SYTACom researchers (Mr. Sharifi Tehrani and his supervisors, Professors Gross and Mannor) to investigate the application of their coding techniques to new applications.