Sirin Tekinay
CCF Division of Computer and Communication Foundations
CSE Directorate for Computer & Information Science & Engineering
Start Date:
February 15, 2001
Expires:
January 31, 2008 (Estimated)
Awarded Amount to Date:
$304890
Investigator(s):
Javier Garcia-Frias jgarcia@eecis.udel.edu (Principal Investigator)
Sponsor:
University of Delaware
210 Hullihen Hall
Newark, DE 19716 302/831-2136
NSF Program(s):
COMMUNICATIONS RESEARCH
Field Application(s):
Program Reference Code(s):
HPCC, 9218, 1045
Program Element Code(s):
4096
ABSTRACT
Error correcting codes (channel codes) are on e of the key elements to optimize digital communications systems. Traditionally, the design of good error correcting codes assumes memoryless channels. In this context, turbo codes and the rediscovery of low-density parity check (LDPC) codes represent two of the most significant advances in channel coding in recent years: Iterative decoding of these codes makes it possible to achieve performance close to the theoretical limits for memoryless channels. However, in most of the applications, the channel is not so simple. This research focuses on the study of iterative decoding for more realistic channels, such as wireless communications channels, characterized by having memory. The objective is to achieve reliable communications, close to theoretical limits, for these types of channels. This will have a direct application in the design of realistic communications systems (including wireless communications), allowing a reduction in the transmitter power requirements for a given quality of service, and a better use of the available bandwidth.
In order to achieve the best possible performance when the channel has memory, the statistical properties of the channel must be exploited in the decoding process. This will be accomplished in a two-fold process: First, statistical models, such as hidden Markov models and stochastic grammars, the iterative decoding schemes will be modified to incorporate the statistical models in the decoding of turbo codes, LDPC codes, and concatenated space-time codes. Both steps are completely interwined. The idea is to jointly design the statistical models and the decoding modifications, taking the decoding performance for the real channel as the real channel as the optimization criterion. Moreover, when possible, this process should work adaptively, with no a priori knowledge of the channel required: when the communications system is used in an unknown channel, a convenient statistical model of the channel should be obtained jointly with decoding (in either a completely blind fashion if possible or by using pilots). In every iteration such a model should be used for the decoding and be conveniently refined.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
F. Vazquez-Araujo, M. Gonzalez-Lopez, L. Castedo, and J. Garcia-Frias. "Serially-Concatenated LDGM Codes for MIMO Channels," IEEE Transactions on Wireless Communications, v.August, 2007, p. 2860.
Gonzalez-Lopez, M; Vazquez-Araujo, FJ; Castedo, L; Garcia-Frias, J. "Serially-concatenated low-density for transmission over AWGN generator matrix (SCLDGM) codes and Rayleigh fading channels," IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.6, 2007, p. 2753-2758.
H. Lou and J. Garcia-Frias. "Low-Density Generator Matrix Codes for Indoor and Markov Channels," IEEE Transactions on Wireless Communications, v.April, 2007, p. 1436.
H. Lou and J. Garcia-Frias. "Rate-Compatible Low-Density Generator Matrix Codes," IEEE Transactions on Communications, v.March, 2008, p. 321.
J. Garcia-Frias. "Decoding of Low-Density Parity Check Codes over Finite-State Binary Markov Channels," IEEE Transactions on Communications, v.Nov., 2004, p. 1840.
J. Garcia-Frias and W. Zhong. "Achieving Near-Shannon Performance by Iterative Decoding of Linear Codes with Low-Density Generator Matrix," IEEE Communications Letters, v.June, 2003, p. 266.
Marsh, AG; Zeng, YJ; Garcia-Frias, J. "The expansion of information in ecological systems: Emergence as a quantifiable state," ECOLOGICAL INFORMATICS, v.1, 2006, p. 107-116.
R. D. Souza and J. Garcia-Frias. "Effect of the Shaping Filter in the Performance of Symbol-Sampled Receivers Over Unknown Continuous-Time Channels," Wireless Personal Communications, v.Sep., 2007, p. 619.
R. D. Souza, J. Garcia-Frias, and R. da Rocha Lopes. "Turbo Equalization for Block Fading MIMO Channels Using Random Signal Mapping," Computers and Electrical Engineering, v.March, 2007, p. 79.
R. Souza and J. Garcia-Frias. "Performance of Symbol-Sampled Receivers over Unknown Continuous-Time Rayleigh Channels," IEEE Transactions on Wireless Communications, v.Sep., 2005, p. 2020.
R. Souza, J. Garcia-Frias, and A. Haimovich. "Semi-Blind EM Based Receivers for Space-Time Coded Modulation and Quasi-Static Frequency Selective Fading Channels," IEEE Transactions on Vehicular Technology, v.July, 2006, p. 1259.
R. Souza, J. Garcia-Frias, and B. Ferreira Uchoa-Filho. "Turbo Equalization for Unknown ISI Channels: A Semiblind Approach," IEEE Latin America, v.June, 2004, p. 1-1.
S. Fu, H. Lou, X.-G. Xia, and J. Garcia-Frias. "LDGM Coded Space-Time Trellis Codes from Differential Encoding," IEEE Communications Letters, v.January, 2007, p. 61.
W. Zhong and J. Garcia-Frias. "LDPC Codes for Compression of Multi-Terminal Sources with Hidden Markov Correlation," IEEE Communications Letters, v.March, 2003, p. 115.
W. Zhu and J. Garcia-Frias. "Stochastic Context-Free Grammars and Hidden Markov Models for Modeling of Bursty Channels," IEEE Transactions on Vehicular Technology, v.May, 2004, p. 666.
