Implementation of a Markov Chain Monte Carlo Based Multiuser/MIMO Detector
Implementation of a Markov Chain Monte Carlo Based Multiuser/MIMO Detector
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DOI：
10.1109/tcsi.2008.925891
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
S. Laraway;B. Farhang-Boroujeny
中科院分区：
文献类型：
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作者：
S. Laraway;B. Farhang-Boroujeny
最近已经开发出使用马尔可夫链蒙特卡罗（MCMC）模拟技术来获得信息位的可能性的多用户/多输入多输出检测器。在本文中，我们探讨了一种此类检测器的实现细节，并提出了一种高效的硬件架构。开发该架构的第一步是导出吉布斯采样器的对数域版本，这是一种获取 MCMC 模拟器样本的有效方法。该公式在数值上稳定并且可以低精度运行。对数域公式也适用于仅涉及加法、减法和比较运算的硬件架构。此外，在所提出的架构中直接引入了流水线。我们还通过计算机模拟探索了所开发架构的字长要求。
Multiuser/multiple-input-multiple-output detectors that use Markov chain Monte Carlo (MCMC) simulation techniques to obtain likelihood of information bits have been developed recently. In this paper, we explore the implementation details of one such detector and present an efficient hardware architecture of it. The first step in development of this architecture is to derive a log-domain version of the Gibbs sampler, an efficient method of obtaining samples of MCMC simulator. This formulation is numerically stable and can operate with low precision. The log- domain formulation also lends itself to a hardware architecture that involves only addition, subtraction, and compare operations. Moreover, pipelining is introduced in the proposed architecture straightforwardly. We also explore the word-length requirement of the developed architecture through computer simulations.