Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection
Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection
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DOI：
10.1007/s11265-017-1313-z
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发表时间：
2017-12
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通讯作者：
Michael Wu;Bei Yin;Kaipeng Li;C. Dick;Joseph R. Cavallaro;Christoph Studer
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作者：
Michael Wu;Bei Yin;Kaipeng Li;C. Dick;Joseph R. Cavallaro;Christoph Studer
与传统蜂窝系统相比，大规模多用户 (MU) MIMO 无线技术有望提高频谱效率。虽然依赖线性均衡的数据检测算法可以为大规模 MU-MIMO 系统实现近乎最佳的错误率性能，但它们需要高吞吐量和低延迟的大型线性系统解决方案，这导致接收机复杂性过高。在本文中，我们研究了各种精确和近似均衡方案，这些方案可以显式（需要计算矩阵逆）或隐式（通过直接计算解向量）求解线性方程组。我们分析了相关的性能/复杂性权衡，并且表明，对于小型基站 (BS) 与用户天线的比率，使用 Cholesky 分解进行精确和隐式数据检测可以在低复杂性下实现接近最优的性能。相比之下，使用近似均衡方法的隐式数据检测可实现大基站与用户天线比率的最佳权衡。通过结合精确、近似、隐式和显式矩阵求逆的优点，我们开发了一种新的频率自适应均衡器（FADE），它在宽带大规模 MU-MIMO 系统的性能和复杂性方面优于现有的数据检测方法。
Massive multi-user (MU) MIMO wireless technology promises improved spectral efficiency compared to that of traditional cellular systems. While data-detection algorithms that rely on linear equalization achieve near-optimal error-rate performance for massive MU-MIMO systems, they require the solution to large linear systems at high throughput and low latency, which results in excessively high receiver complexity. In this paper, we investigate a variety of exact and approximate equalization schemes that solve the system of linear equations eitherexplicitly(requiring the computation of a matrix inverse) orimplicitly(by directly computing the solution vector). We analyze the associated performance/complexity trade-offs, and we show that for small base-station (BS)-to-user-antenna ratios, exact and implicit data detection using the Cholesky decomposition achieves near-optimal performance at low complexity. In contrast, implicit data detection using approximate equalization methods results in the best trade-off for large BS-to-user-antenna ratios. By combining the advantages of exact, approximate, implicit, and explicit matrix inversion, we develop a newfrequency-adaptiveequalizer (FADE), which outperforms existing data-detection methods in terms of performanceandcomplexity for wideband massive MU-MIMO systems.