论文标题
使用模拟rrAM矩阵计算的极快，节能的巨大模拟编码
Extremely-Fast, Energy-Efficient Massive MIMO Precoding with Analog RRAM Matrix Computing
论文作者
论文摘要
无线通信中的信号处理，例如预编码，检测和通道估计，基本上是关于解决逆矩阵问题的问题，但是，在传统的数字计算机中，这些问题在较慢且效率低下，因此需要自由基的范式转移才能实现快速，实时的解决方案。在这里，我们第一次将新兴的模拟矩阵计算（AMC）应用于大型MIMO的线性预编码。实现的AMC概念扩展到处理复杂值的信号。为了使MIMO通道模型适应RRAM电导映射，开发了一个新的矩阵反转电路。此外，完全模拟数据流和优化的操作放大器旨在支持AMC预编码实现。仿真结果表明，对于16x128 MIMO系统，零孔的预编码被求解在20 ns之内，这比传统数字方法快两个数量级。同时，能源效率提高了50倍。
Signal processing in wireless communications, such as precoding, detection, and channel estimation, are basically about solving inverse matrix problems, which, however, are slow and inefficient in conventional digital computers, thus requiring a radical paradigm shift to achieve fast, real-time solutions. Here, for the first time, we apply the emerging analog matrix computing (AMC) to the linear precoding of massive MIMO. The real-valued AMC concept is extended to process complex-valued signals. In order to adapt the MIMO channel models to RRAM conductance mapping, a new matrix inversion circuit is developed. In addition, fully analog dataflow and optimized operational amplifiers are designed to support AMC precoding implementation. Simulation results show that the zero-forcing precoding is solved within 20 ns for a 16x128 MIMO system, which is two orders of magnitude faster than the conventional digital approach. Meanwhile, the energy efficiency is improved by 50x.
