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Block Markov Superposition Transmission: A Simple and Flexible Method for Constructing Good Codes

Event Date: February 2, 2017
Speaker: Professor Xiao Ma
Speaker Affiliation: Sun Yat-sen University, Guangzhou, China
Type: CNSIP Area Seminar
Time: 2:30pm
Location: MSEE 239
Contact Name: Professor Xiaojun Lin
Contact Phone: 765-49-40626
Contact Email: linx@purdue.edu
Priority: No
School or Program: Electrical and Computer Engineering
College Calendar: Show

Abstract

Block Markov Superposition Transmission (BMST) codes are a class of spatially coupled codes constructed from short codes, where the generator matrices of the involved short codes (referred to as basic codes) are coupled. The encoding process of BMST can be as fast as that of the basic code, while the decoding process can be implemented as an iterative sliding-window decoding (SWD) algorithm with a tunable delay. More importantly, BMST codes have a simple lower bound that relates the code performance to that of the short code and the transmission memory. Simulations as well as threshold analysis show that the lower bounds can be matched with a moderate decoding delay in the low bit-error-rate (BER) region, implying that the iterative SWD algorithm is near optimal. BMST codes can also admit a two-phase decoding (TPD) algorithm, whose performance in the low BER region can be upper-bounded. It has been verified by simulation that the construction approach is applicable not only to binary phase-shift keying (BPSK) modulation but also to bit-interleaved coded modulation (BICM), spatial modulation, continuous phase modulation (CPM) and intensity modulation in visible light communications (VLC). In addition, BMST codes can be used to construct good multiple-rate codes for wide region of code rates, e.g., BMST with Hadamard transform (HT) coset codes, BMST with time-sharing repetition and/or single-parity-check (RSPC) codes, BMST with time-sharing nonbinary repetition and/or uncoded transmission (RUN) codes, systematic BMST with punctured repetition codes.

Biography

Dr. Xiao Ma is a Professor with the School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China. He received the Ph.D. degree in communication and information systems from Xidian University, China, in 2000. From 2000 to 2002, he was a Postdoctoral Fellow with Harvard University, Cambridge, MA. From 2002 to 2004, he was a Research Fellow with City University of Hong Kong.

Dr. Ma’s research interests include information theory, channel coding theory and their applications to communication systems and digital recording systems. Dr. Ma is a corecipient, with A. Kavcic and N. Varnica, of the 2005 IEEE Best Paper Award in Signal Processing and Coding for Data Storage. In 2006, Dr. Ma received the Microsoft Professorship Award from Microsoft Research Asia. Dr. Ma is a member of the IEEE.