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| Rapid Acquisition of Gold Codes and Related Sequences using Iterative Message Passing on Redundant Graphical Models | |||
| Principe,Fabio | Dipartimento di Ingegneria dell'Informazione - University of Pisa | ||
| Luise,Marco | Dipartimento di Ingegneria dell'Informazione - University of Pisa | ||
| Chugg,Keith M. | Communication Sciences Institute, Electrical Engineering Dept. - University of Southern California | ||
| Fast acquisition of long pseudo-noise (PN) sequences is an important problem in many military and civilian communication systems. Zhu and Chugg (Milcom 2003) recently demonstrated that methods originating in iterative decoding can be applied to rapidly acquire PN sequences with low complexity. These methods are based on modeling the structure of the sequence with a cyclic graphical model, typically a Tanner graph corresponding to a set of parity check equations satisfied by the sequence. Follow-on work showed that significant benefits can be obtained using redundant parity checks corresponding to redundant graphical models (c.f. Yeung and Chugg, Allerton 2005). This previous work has focused on linear feedback shift register (LFSR) sequences that have sparse feedback polynomials. In this work we address the problem of fast acquisition to Gold sequences and LFSR sequences with non-sparse generators. Since a Gold sequence can be described by a higher-order LFSR (typically non-sparse) generator, these problems are closely related. The approach considered is to search for non-primitive, higher-order generator polynomials that are sparse and then use these to construct redundant graphical models. In this paper we present a method for searching for such sparse non-primitive generators and show the benefits of using these in redundant models through computer simulation. We also propose another distinct approach for acquiring Gold codes using iterative methods based on a hierarchal model for the two LFSR generators that comprise a Gold code. | |||
| Keith M. Chugg (S'88-M'95) received the B.S. degree (high distinction) in Engineering from Harvey Mudd College, Claremont, CA in 1989 and the M.S. and Ph.D. degrees in Electrical Engineering (EE) from USC, Los Angeles, CA in 1990 and 1995, respectively. During the 1995-1996 academic year he was an Assistant Professor with the Electrical and Computer Engineering Dept., University of Arizona, Tucson, AZ. In 1996 he joined the EE Dept. at USC in 1996 where he is currently an Associate Professor. His research interests are in the general areas of signaling, detection, and estimation for digital communication and data storage systems. He is also interested in architectures for efficient implementation of the resulting algorithms. Along with his former Ph.D. students, A. Anastasopoulos and X. Chen, he is co-author of the book Iterative Detection: Adaptivity, Complexity Reduction, and Applications (Norwell, MA: Kluwer). He is a co-founder of TrellisWare Technologies, Inc., where he is Chief Scientist. He has served as an associate editor for the IEEE Transactions on Communications and was Program Co-Chair for the Communication Theory Symposium at Globecom 2002. He received the Fred W. Ellersick award for the best unclassified paper at MILCOM 2003. | |||