相关Rician信道下无小区大规模MIMO系统的最优双线性均衡器
Optimal Bilinear Equalizer for Cell-Free Massive MIMO Systems over Correlated Rician Channels
AI总结：
本文针对相关Rician信道下的无小区大规模MIMO系统，设计了低复杂度的最优双线性均衡器（OBE）合并方案，推导了闭包频谱效率表达式，并提出一种集中式和两种分布式OBE方案以最大化SE，数值结果表明其在严重导频污染下仍能保持优异性能。
摘要：
本文探讨了在具有空间相关Rician衰落信道的无小区大规模多输入多输出网络中，低复杂度最优双线性均衡器（OBE）合并方案的设计。我们为应用了双线性均衡器（BE）结构合并方案的集中式和分布式处理方案提供了频谱效率（SE）性能分析框架。BE结构合并是一组由基于信道统计的BE矩阵与瞬时信道估计相乘构建的方案。值得注意的是，我们推导了集中式和分布式BE结构合并方案的闭包可达SE表达式。我们提出了一种集中式和两种分布式OBE方案：集中式OBE（C-OBE）、基于全局信道统计的分布式OBE（DG-OBE）和基于局部信道统计的分布式OBE（DL-OBE），它们分别最大化各自的SE表达式。这些方案中的OBE矩阵根据不同级别的信道统计进行定制。值得注意的是，我们为C-OBE、DG-OBE和DL-OBE合并方案获得了新颖且有洞察力的闭包结果。数值结果表明，所提出的OBE方案能够实现优异的SE，即使在存在严重导频污染的场景中也是如此。
英文摘要：
In this paper, we explore the low-complexity optimal bilinear equalizer (OBE) combining scheme design for cell-free massive multiple-input multiple-output networks with spatially correlated Rician fading channels. We provide a spectral efficiency (SE) performance analysis framework for both the centralized and distributed processing schemes with bilinear equalizer (BE)-structure combining schemes applied. The BE-structured combining is a set of schemes that are constructed by the multiplications of channel statistics-based BE matrices and instantaneous channel estimates. Notably, we derive closed-form achievable SE expressions for centralized and distributed BE-structured combining schemes. We propose one centralized and two distributed OBE schemes: Centralized OBE (C-OBE), Distributed OBE based on Global channel statistics (DG-OBE), and Distributed OBE based on Local channel statistics (DL-OBE), which maximize their respective SE expressions. OBE matrices in these schemes are tailored based on varying levels of channel statistics. Notably, we obtain new and insightful closed-form results for the C-OBE, DG-OBE, and DL-OBE combining schemes. Numerical results demonstrate that the proposed OBE schemes can achieve excellent SE, even in scenarios with severe pilot contamination.
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