Generalized Successive Interference Cancellation/Matching Pursuits Algorithm for DS-CDMA Array-Based Radiolocation and Telemetry
dc.contributor.author | Iltis, Ronald A. | |
dc.contributor.author | Kim, Sunwoo | |
dc.date.accessioned | 2016-04-14T20:06:58Z | en |
dc.date.available | 2016-04-14T20:06:58Z | en |
dc.date.issued | 2003-10 | en |
dc.identifier.issn | 0884-5123 | en |
dc.identifier.issn | 0074-9079 | en |
dc.identifier.uri | http://hdl.handle.net/10150/605362 | en |
dc.description | International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada | en_US |
dc.description.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. | |
dc.description.sponsorship | International Foundation for Telemetering | en |
dc.language.iso | en_US | en |
dc.publisher | International Foundation for Telemetering | en |
dc.relation.url | http://www.telemetry.org/ | en |
dc.rights | Copyright © International Foundation for Telemetering | en |
dc.subject | Code-division multiple access | en |
dc.subject | radiolocation | en |
dc.subject | channel estimation | en |
dc.title | Generalized Successive Interference Cancellation/Matching Pursuits Algorithm for DS-CDMA Array-Based Radiolocation and Telemetry | en_US |
dc.type | text | en |
dc.type | Proceedings | en |
dc.contributor.department | University of California | en |
dc.identifier.journal | International Telemetering Conference Proceedings | en |
dc.description.collectioninformation | 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. | en |
refterms.dateFOA | 2018-05-29T08:00:13Z | |
html.description.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. |