Generalized Successive Interference Cancellation/Matching Pursuits Algorithm for DS-CDMA Array-Based Radiolocation and Telemetry

Persistent Link:
http://hdl.handle.net/10150/605362
Title:
Generalized Successive Interference Cancellation/Matching Pursuits Algorithm for DS-CDMA Array-Based Radiolocation and Telemetry
Author:
Iltis, Ronald A.; Kim, Sunwoo
Affiliation:
University of California
Issue Date:
2003-10
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
A radiolocation problem using DS-CDMA waveforms with array-based receivers is considered. It is assumed that M snapshots of N(s) Nyquist sample long data are available, with a P element antenna array. In the handshaking radiolocation protocol assumed here, data training sequences are available for all K users. As a result, the received spatial-temporal matrix R ∈ C^(MN(s)x P) is approximated by a sum of deterministic signal matrices S(k)^b ∈ C^(MN(s) N(s)) multiplied by unconstrained array response matrices A(k) ∈ C^(N(s)x P). The unknown delays are not estimated directly. Rather, the delays are implicitly approximated as part of the symbol-length long channel, and solutions sparse in the rows of A are thus sought. The resulting ML cost function is J = ||R - ∑(k=1)^K S(k)^bA(k)||(F). The Generalized Successive Interference Cancellation (GSIC) algorithm is employed to iteratively estimate and cancel multiuser interference. Thus, at the k-th GSIC iteration, the index p(k) = arg min(l ≠ p(1),...,p(k-1)) {min(A(l)) ||R^k-S(l)^bA(l)||(F)} is computed, where R^k = ∑(l=1)^(k-1) S(pl)^bÂ(pl). Matching pursuits is embedded in the GSIC iterations to compute sparse channel/steering vector solutions Â(l). Simulations are presented for DS-CDMA signals received over channels computed using a ray-tracing propagation model.
Keywords:
Code-division multiple access; radiolocation; channel estimation
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleGeneralized Successive Interference Cancellation/Matching Pursuits Algorithm for DS-CDMA Array-Based Radiolocation and Telemetryen_US
dc.contributor.authorIltis, Ronald A.en
dc.contributor.authorKim, Sunwooen
dc.contributor.departmentUniversity of Californiaen
dc.date.issued2003-10en
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractA radiolocation problem using DS-CDMA waveforms with array-based receivers is considered. It is assumed that M snapshots of N(s) Nyquist sample long data are available, with a P element antenna array. In the handshaking radiolocation protocol assumed here, data training sequences are available for all K users. As a result, the received spatial-temporal matrix R ∈ C^(MN(s)x P) is approximated by a sum of deterministic signal matrices S(k)^b ∈ C^(MN(s) N(s)) multiplied by unconstrained array response matrices A(k) ∈ C^(N(s)x P). The unknown delays are not estimated directly. Rather, the delays are implicitly approximated as part of the symbol-length long channel, and solutions sparse in the rows of A are thus sought. The resulting ML cost function is J = ||R - ∑(k=1)^K S(k)^bA(k)||(F). The Generalized Successive Interference Cancellation (GSIC) algorithm is employed to iteratively estimate and cancel multiuser interference. Thus, at the k-th GSIC iteration, the index p(k) = arg min(l ≠ p(1),...,p(k-1)) {min(A(l)) ||R^k-S(l)^bA(l)||(F)} is computed, where R^k = ∑(l=1)^(k-1) S(pl)^bÂ(pl). Matching pursuits is embedded in the GSIC iterations to compute sparse channel/steering vector solutions Â(l). Simulations are presented for DS-CDMA signals received over channels computed using a ray-tracing propagation model.en
dc.subjectCode-division multiple accessen
dc.subjectradiolocationen
dc.subjectchannel estimationen
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/605362en
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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