Joint Beamforming and Matching for Ultra-Dense Massive Antenna Arrays

TL;DR

The paper tackles the high cost and power demands of scaling MIMO to ultra-dense antenna arrays by introducing a physically consistent REMS framework and a switch-based joint beamforming and matching architecture. It models the RF frontend, tuning network, and radiating structure to predict system behavior efficiently, and proposes a 4×4/16×16 tile-based architecture that uses triple-stub tuners and RF switches to perform analog beamforming while sharing a single PA per tile. Through full-wave simulations and the REMS metrics, the authors demonstrate that the proposed approach can closely approach the antenna gain of all-digital systems, while reducing RF chains by up to a factor of 16 and lowering cost and power. The work also provides a structured methodology for evaluating gain losses due to non-ideal matching and switching, and it shows favorable scaling for very large arrays, indicating practical viability for next-generation wireless systems.

Abstract

Massive multiple-input multiple-output (MIMO) offers substantial spectral-efficiency gains, but scaling to very large antenna arrays with conventional all-digital and hybrid beamforming architectures quickly results in excessively high costs and power consumption. Low-cost, switch-based architectures have recently emerged as a potential alternative. However, prior studies rely on simplified models that ignore (among others) antenna coupling, radiation patterns, and matching losses, resulting in inaccurate performance predictions. In this paper, we use a physically consistent electromagnetic modeling framework to analyze an ultra-dense patch-antenna array architecture that performs joint beamforming and matching using networks of inexpensive RF switches. Our results demonstrate that simple, switch-based beamforming architectures can approach the antenna-gain of all-digital solutions at significantly lower cost and complexity.

Figures (10)

• Figure 1: Structure of the model used in this paper. The RF frontend represents $N$ power amplifiers; the tuning network represents reconfigurable analog beamforming and matching RF circuitry; and the radiating structure represents $M$ antenna elements. The original structure shown in stutz_schwan_studer_efficient_and_physically_consistent_modeling_of_reconfigurable_electromagnetic_structures additionally models low-noise amplifiers (for receivers), noise from various sources, and incoming far-field waves---all of which are not used here.
• Figure 2: Signal-flow graph of the model used in this paper. The nodes represent (i) complex vectors corresponding to voltages and circuit-theoretic power waves, and (ii) elements in an $L^2$-space that describe the far-field radiation pattern of the outgoing electromagnetic waves. The edges denote bounded linear operators acting between the respective spaces. The original graph shown in stutz_schwan_studer_efficient_and_physically_consistent_modeling_of_reconfigurable_electromagnetic_structures additionally contains received voltages, influence from various noise sources, and incoming far-field waves.
• Figure 3: The relationships between the power metrics, including the radiating intensity, are illustrated with solid blue lines. The REMS gain, tuning gain, and radiating gain, which relate the radiation intensity to the corresponding power quantities, are shown with a dashed green line. This figure extends stutz_schwan_studer_efficient_and_physically_consistent_modeling_of_reconfigurable_electromagnetic_structures by additionally including the tuning and radiating gain.
• Figure 4: Screenshots from Ansys HFSS of the used radiating structures: A $4\times4$ and a $16\times16$ ultra dense arrays of square patch antennas with an inter-element spacing of $\frac{\lambda}{4}$. The arrays lie on the $\theta = 90^\circ$ plane.
• Figure 5: Radiating structure gain $\hat{G}_{\textnormal{R}}(\theta,\varphi)$ of the used radiating structures for $(\theta,\varphi) \in [0, \pi/2] \times [0, 2\pi)$.

Theorems & Definitions (6)

• Remark 1: cf. [1, Rem. 6]
• Definition 1: Tuning Gain
• Definition 2: Radiating Gain
• Remark 2
• Remark 3
• Remark 4