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

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / 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.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/605362
Date10 1900
CreatorsIltis, Ronald A., Kim, Sunwoo
ContributorsUniversity of California
PublisherInternational Foundation for Telemetering
Source SetsUniversity of Arizona
Languageen_US
Detected LanguageEnglish
Typetext, Proceedings
RightsCopyright © International Foundation for Telemetering
Relationhttp://www.telemetry.org/

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