On the performance of mismatched data detection in large MIMO systems
On the performance of mismatched data detection in large MIMO systems
复制标题
大型MIMO系统中失配数据检测的性能研究
DOI：
10.1109/isit.2016.7541285
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Christoph Studer
中科院分区：
文献类型：
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作者：
Charles Jeon;A. Maleki;Christoph Studer
我们研究了大型多输入多输出（MIMO）系统中不匹配数据检测的性能，其中数据检测器中使用的发送信号的先验分布与真实先验不同。为了最大限度地减少这种先前的不匹配所造成的性能损失，我们包括一个调整阶段到我们最近提出的大MIMO近似消息传递（LAMA）算法，这使我们能够开发不匹配的LAMA算法与最佳以及次最佳的调整。我们表明，精心选择的先验往往使更简单和计算更有效的算法相比，LAMA与真正的先验，同时实现接近最佳的性能。我们的算法的高斯先验和均匀先验的超立方体覆盖的QAM星座的性能分析恢复线性和非线性MIMO数据检测的经典和最近的结果，分别。
We investigate the performance of mismatched data detection in large multiple-input multiple-output (MIMO) systems, where the prior distribution of the transmit signal used in the data detector differs from the true prior. To minimize the performance loss caused by this prior mismatch, we include a tuning stage into our recently-proposed large MIMO approximate message passing (LAMA) algorithm, which allows us to develop mismatched LAMA algorithms with optimal as well as sub-optimal tuning. We show that carefully-selected priors often enable simpler and computationally more efficient algorithms compared to LAMA with the true prior while achieving near-optimal performance. A performance analysis of our algorithms for a Gaussian prior and a uniform prior within a hypercube covering the QAM constellation recovers classical and recent results on linear and non-linear MIMO data detection, respectively.