On the achievable rates of decentralized equalization in massive MU-MIMO systems
On the achievable rates of decentralized equalization in massive MU-MIMO systems
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DOI：
10.1109/isit.2017.8006699
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发表时间：
2017-05
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影响因子：
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通讯作者：
Charles Jeon;Kaipeng Li;Joseph R. Cavallaro;Christoph Studer
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文献类型：
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作者：
Charles Jeon;Kaipeng Li;Joseph R. Cavallaro;Christoph Studer
与传统的小规模 MIMO 技术相比，大规模多用户 (MU) 多输入多输出 (MIMO) 有望显着提高频谱效率。线性均衡算法，例如基于迫零 (ZF) 或最小均方误差 (MMSE) 的方法，通常依赖于基站 (BS) 的集中处理，这会导致 (i) 互连和芯片输入/输出数据速率过高，以及 (ii) 高计算复杂性。在本文中，我们研究了缓解这两个问题的分散均衡的可实现率。我们考虑两种不同的基站架构，将天线阵列划分为集群，每个集群与独立的射频链和信号处理硬件相关联，每个集群的结果都融合在前馈网络中。对于这两种架构，我们考虑了 ZF、MMSE 和一种基于近似消息传递 (AMP) 的新型非线性均衡算法，并从理论上分析了这些方法可实现的速率。我们的结果表明，与集中式解决方案相比，使用我们基于 AMP 的方法进行去中心化均衡在可实现的速率方面不会造成损失或损失可以忽略不计。
Massive multi-user (MU) multiple-input multiple-output (MIMO) promises significant gains in spectral efficiency compared to traditional, small-scale MIMO technology. Linear equalization algorithms, such as zero forcing (ZF) or minimum mean-square error (MMSE)-based methods, typically rely on centralized processing at the base station (BS), which results in (i) excessively high interconnect and chip input/output data rates, and (ii) high computational complexity. In this paper, we investigate the achievable rates of decentralized equalization that mitigates both of these issues. We consider two distinct BS architectures that partition the antenna array into clusters, each associated with independent radio-frequency chains and signal processing hardware, and the results of each cluster are fused in a feed forward network. For both architectures, we consider ZF, MMSE, and a novel, non-linear equalization algorithm that builds upon approximate message passing (AMP), and we theoretically analyze the achievable rates of these methods. Our results demonstrate that decentralized equalization with our AMP-based methods incurs no or only a negligible loss in terms of achievable rates compared to that of centralized solutions.