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A robust rank estimation algorithm of group-blind MMSE multiuser detectors for CDMA systems

机译:CDMA系统中组盲MMSE多用户检测器的鲁棒秩估计算法

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摘要

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.
机译:我们为加性白色或彩色高斯噪声模型提出了一种自适应秩估计方法。本文的主要贡献包括三个部分。 (1)我们研究了Wang和Host-Madsen的群盲多用户检测器中的秩失配问题(请参阅IEEE J. Select。Areas Commun。,第17卷,第1971-1984页,1999年11月),并找到低估等级会导致性能显着下降,而等级高估可以在低信噪比(SNR)区域实现性能提升。但是,秩过高估计会导致不正确的信道估计,这会严重降低高SNR区域中的检测器性能。 (2)我们提出了一种用于初始秩估计的启发式准则,该准则对于非白噪声情况是鲁棒的。 (3)为了缓解秩不匹配问题,我们针对秩和信号子空间决策引入了假设检验准则,该准则为群盲检测器选择了最可能的秩。仿真结果表明,采用这种自适应秩估计算法的群盲检测器的性能可与具有完全秩知识的群盲媲美,甚至在中低SNR区域甚至更好。

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