Abstract
We propose an adaptive rank-estimation method for the additive white or colored Gaussian noise model. The main contribution of this paper has three parts. (1) We investigate the rank mismatch problem in the group-blind multiuser detector of Wang and Host-Madsen (see IEEE J. Select. Areas Commun., vol.17, p.1971-1984, Nov. 1999), and find that underestimating the rank causes significant performance degradation, whereas, rank overestimation can achieve performance gain in the low signal-to-noise-ratio (SNR) region. However, rank overestimation can lead to inaccurate channel estimation, which degrades the detector performance significantly in the high SNR region. (2) We propose a heuristic criterion for initial rank estimation which is robust for nonwhite noise cases. (3) In order to mitigate the rank mismatch problem, we introduce a hypothesis testing criterion for rank and signal subspace decisions, which selects the most probable rank for the group-blind detectors. Simulation results show that the performance of the group-blind detector using this adaptive rank estimation algorithm is comparable to the group-blind with perfect knowledge of the rank, and even better in the low-to-medium SNR region.
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