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

• Main Authors: Iltis, Ronald A., Kim, Sunwoo
• Other Authors: University of California
• Language: en_US
• Published: International Foundation for Telemetering 2003
• Subjects: Code-division multiple access; radiolocation; channel estimation
• Online Access: http://hdl.handle.net/10150/605362; http://arizona.openrepository.com/arizona/handle/10150/605362

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.