Markov Chain Monte Carlo based multiuser/MIMO detector: 802.11ac implementation and measurement
Markov Chain Monte Carlo based multiuser/MIMO detector: 802.11ac implementation and measurement
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基于马尔可夫链蒙特卡罗的多用户/MIMO 检测器：802.11ac 实施和测量
DOI：
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发表时间：
2015
期刊：
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通讯作者：
B. Farhang
中科院分区：
文献类型：
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作者：
Jonathan C. Hedstrom;C. Yuen;B. Farhang
无线通信系统对更好的、低复杂度的检测器有强烈需求。在此，我们展示了在802.11ac WiFi框架内一种称为马尔可夫链蒙特卡罗（MCMC）的近最优近似最大似然（ML）方法的实现、模拟以及实际测量。详细阐述了信噪比（SNR）、信道矩阵条件数（CN）和误比特率（BER）之间的关系。论证了在实际测量中考虑条件数的重要性。
There is a strong need in wireless communication systems for better, low-complexity detectors. Here we demonstrate the implementation, simulation, and real-world measurements of such a near-optimal approximate ML method called Markov Chain Monte Carlo (MCMC) within an 802.11ac WiFi framework. Detail is provided on the relationship between SNR, channel matrix condition number (CN), and bit error rate (BER). The importance of considering condition number in real-world measurements is demonstrated.