Extremely-Fast, Energy-Efficient Massive MIMO Precoding With Analog RRAM Matrix Computing

Signal processing in wireless communications, such as precoding, detection, and channel estimation, are basically about solving inverse matrix problems, which, however, slow inefficient conventional digital computers, thus requiring a radical paradigm shift to achieve fast, real-time solutions. Here, for the first time, we apply emerging analog computing (AMC) linear precoding of massive MIMO. The real-valued AMC concept is extended process complex-valued signals. In order adapt MIMO models RRAM conductance mapping, new inversion circuit developed. addition, fully dataflow optimized operational amplifiers designed support implementation. Simulation results show that zero-forcing solved within 20 ns $16\times 128$ system, which two orders magnitude faster than approach. Meanwhile, energy efficiency improved by notation="LaTeX">$50\times $ .