Accelerating massive MIMO in 6G communications by analog in-memory computing circuits

Wireless communication systems are the backbone of today's digital society. To achieve unprecedented throughput and efficiency, 5G and 6G networks will leverage parallel communication over multiple spatial channels under the massive MIMO (multiple-input multiple-output) framework. One of the main limitations of MIMO is its heavy load of matrix operations, a task for which von Neumann-based computers are deeply unoptimized. This bottleneck can be solved by in-memory computing (IMC), where computation is performed directly within the memory, thus eliminating the constant data shuttling between the memory and the processing unit. Here, we provide an experimental validation of a closed-loop IMC (CL-IMC) system on a 90 nm CMOS integrated circuit. Zero-forcing and regularized-zero-forcing decoding are executed with $14\times 7$ MIMO link. The hardware demonstration shows 99.91% accuracy, which is close to a floating-point precision decoder. These results support CL-IMC as a promising candidate for data processing in massive MIMO for next-generation cellular networks.