Towards 6G MIMO: Massive Spatial Multiplexing, Dense Arrays, and Interplay Between Electromagnetics and Processing

TL;DR

This paper explores the development of next-generation 6G MIMO technology, emphasizing massive spatial multiplexing, dense arrays, and the integration of electromagnetics with signal processing to address future wireless demands.

Contribution

It provides a comprehensive overview of ultra-massive MIMO, including new propagation phenomena, channel estimation methods, and the co-design of antennas and processing, bridging communication, EM, and circuit theories.

Findings

Massive multiplexing enabled by near-field effects

Characterization of spatial degrees-of-freedom in dense arrays

Practical channel estimation schemes for large antenna systems

Abstract

The increasing demand for wireless data transfer has been the driving force behind the widespread adoption of Massive MIMO (multiple-input multiple-output) technology in 5G. The next-generation MIMO technology is now being developed to cater to the new data traffic and performance expectations generated by new user devices and services in the next decade. The evolution towards "ultra-massive MIMO (UM-MIMO)" is not only about adding more antennas but will also uncover new propagation and hardware phenomena that can only be treated by jointly utilizing insights from the communication, electromagnetic (EM), and circuit theory areas. This article offers a comprehensive overview of the key benefits of the UM-MIMO technology and the associated challenges. It explores massive multiplexing facilitated by radiative near-field effects, characterizes the spatial degrees-of-freedom, and practical channel estimation schemes tailored for massive arrays. Moreover, we provide a tutorial on EM theory and circuit theory, and how it is used to obtain physically consistent antenna and channel models. Subsequently, the article describes different ways to implement massive and dense antenna arrays, and how to co-design antennas with signal processing. The main open research challenges are identified at the end.