All-digital basestation (BS) architectures enable superior spectral efficiency compared to hybrid solutions in massive multi-user MIMO systems. However, supporting large bandwidths with all-digital architectures at mmWave frequencies is challenging as traditional baseband processing would result in excessively high power consumption and large silicon area. The recently-proposed concept of finite-alphabet equalization is able to address both of these issues by using equalization matrices that contain low-resolution entries to lower the power and complexity of high-throughput matrix-vector products in hardware. In this paper, we explore two different finite-alphabet equalization hardware implementations that tightly integrate the memory and processing elements: (i) a parallel array of multiply-accumulate (MAC) units and (ii) a bit-serial processing-in-memory (PIM) architecture. Our all-digital VLSI implementation results in 28nm CMOS show that the bit-serial PIM architecture reduces the area and power consumption up to a factor of 2x and 3x, respectively, when compared to a parallel MAC array that operates at the same throughput.
@article{arxiv.2009.03874,
title = {High-Bandwidth Spatial Equalization for mmWave Massive MU-MIMO with Processing-In-Memory},
author = {Oscar Castañeda and Sven Jacobsson and Giuseppe Durisi and Tom Goldstein and Christoph Studer},
journal= {arXiv preprint arXiv:2009.03874},
year = {2020}
}
Comments
To be presented at the IEEE International Symposium on Circuits and Systems (ISCAS) 2020; invited to a special issue in the IEEE Transactions on Circuits and Systems (TCAS)-II