Reduced-rank multistage receivers for DS-CDMA in frequency-selective fading channels

Sau-Hsuan Wu*, Urbashi Mitra, C. C.Jay Kuo

*Corresponding author for this work

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Multistage (MS) implementation of the minimum mean-square error (MMSE), minimum output energy (MOE), best linear unbiased estimation (BLUE), and maximum-likelihood (ML) filter banks (FBs) is developed based on the concept of the MS Wiener filtering (MSWF) introduced by Goldstein et al. These FBs are shown to share a common MS structure for interference suppression, modulo a distinctive scaling matrix at each filter's output. Based on this finding, a framework is proposed for joint channel estimation and multiuser detection (MUD) in frequency-selective fading channels. Adaptive reduced-rank equal gain combining (EGC) schemes for this family of FBs (MMSE, MOE, BLUE, and ML) are proposed for noncoherent blind MUD of direct-sequence code-division multiple-access systems, and contrasted with the maximal ratio combining counterparts that are also formed with the proposed common structure under the assumption of known channel-state information. The bit-error rate, steady-state output signal-to-interference plus noise ratio (SINR), and convergence of the output SINRs are investigated via computer simulation. Simulation results indicate that the output SINRs attain full-rank performance with much lower rank for a highly loaded system, and that the adaptive reduced-rank EGC BLUE/ML FBs outperform the EGC MMSE/MOE FBs, due to the unbiased nature of the implicit BLUE channel estimators employed in the EGC BLUE/ML schemes.

Original languageEnglish
Pages (from-to)366-378
Number of pages13
JournalIEEE Transactions on Communications
Volume53
Issue number2
DOIs
StatePublished - 1 Feb 2005

Keywords

  • Best linear unbiased estimation (BLUE)
  • Code-division multiple access (CDMA)
  • Maximum-likelihood (ML)
  • Minimum mean-square error (MMSE)
  • Minimum output energy (MOE)
  • Multipath fading channels
  • Multistage Wiener filtering (MSWF)
  • Multiuser detection (MUD)
  • Reduced-rank filtering
  • Time-varying channels

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