From Antenna Abundance to Antenna Intelligence in 6G Gigantic MIMO Systems

TL;DR

It is demonstrated how superior multiuser MIMO performance can be achieved with far fewer antennas by exploiting non-uniform sparse arrays with site-specific antenna placements based on either pre-optimized irregular arrays or real-time movable antennas.

Abstract

Current cellular systems achieve high spectral efficiency through Massive MIMO, which leverages an abundance of antennas to create favorable propagation conditions for multiuser spatial multiplexing. Looking towards future networks, the extrapolation of this paradigm leads to systems with many hundreds of antennas per base station, raising concerns regarding hardware complexity, cost, and power consumption. This article suggests more intelligent array designs that reduce the need for excessive antenna numbers. We revisit classical uniform array design principles and explain how their uniform spatial sampling leads to unnecessary redundancies in practical deployment scenarios. By exploiting non-uniform sparse arrays with site-specific antenna placements -- based on either pre-optimized irregular arrays or real-time movable antennas -- we demonstrate how superior multiuser MIMO performance can be achieved with far fewer antennas. These principles are inspired by previous works on wireless localization. We explain and demonstrate numerically how these concepts can be adapted for communications to improve the average sum rate and similar metrics. The results suggest a paradigm shift for future antenna array design, where antenna intelligence replaces sheer antenna count. This opens new opportunities for efficient, adaptable, and sustainable Gigantic MIMO systems.

Figures (6)

• Figure 1: Massive MIMO in 5G builds on having an antenna abundance. As shown in (a), the sum rate with RZF beamforming becomes close to the interference-free bound when $M/K \geq 4$. The practical BS shown in (b) has $M=32$ dual-polarized antennas, each comprising two discrete radiating elements (drawn as crosses) to enhance the antenna gain. This BS is designed to support $M/K=4$.
• Figure 2: A carrier wave with a fixed wavelength $\lambda$ gives rise to different apparent wavelengths when observed on a line or plane. (a) illustrates how the apparent wavelength varies with the incident angle. (b) shows how the mapping between incident angles and apparent spatial frequencies. The shaded region demonstrates the nonlinearity of the mapping. (c) shows the corresponding mapping for a planar array.
• Figure 3: The beampatterns when transmitting in two different directions using a ULA with $8$ antennas. The array gain is independent of the antenna spacing $\Delta$, but the beamwidth shrinks as it increases, resulting in more and larger sidelobes.
• Figure 4: Non-uniform arrays can follow different design principles, using different features and optimizing different metrics.
• Figure 5: A comparison of the uplink sum rate achieved with six linear arrays in a LOS scenario with random user angles. The ULAs are outperformed by the non-uniform arrays, but the array with MAs provides the highest rates.