Signal Processing Foundations of Reconfigurable Antennas in the Tri-Hybrid MIMO Architecture

To enable larger apertures in multipleinput multipleoutput MIMO systems the trihybrid MIMO architecture offers a promising lowcost and lowpower solution by introducing reconfigurable antennas as a third layer of precoding on top of conventional digital and analog processing In this paper we develop a unified signal processing framework for trihybrid MIMO that explicitly captures the electromagnetic EM characteristics of diverse reconfigurable antenna technologies We first propose a generic inputoutput model that incorporates the reconfigurable antenna layer into an effective channel representation revealing a fundamental coupling between the channel precoder and radiated power Building on this model we formulate a general optimization problem that jointly accounts for digital analog and antennadomain precoding under hardware and power constraints We then instantiate this framework across seven representative reconfigurable antenna architectures including parasitic arrays dynamic metasurface antennas fluidpixel antennas polarizationreconfigurable antennas stacked intelligent metasurfaces pinching antenna systems and nonradiating wires To systematically compare these heterogeneous architectures we introduce a new metric the reconfigurability efficiency factor REF which quantifies the performance gains achievable through antenna reconfiguration under realistic constraints Numerical results demonstrate the tradeoffs among aperture size power consumption hardware complexity and spectral efficiency Our results establish that EMlevel reconfiguration reshapes the signal processing design space highlighting the need for new architectures and algorithms that jointly optimize across digital analog and electromagnetic domains This work reveals that electromagnetic reconfiguration couples the channel and precoder

Beamforming with hybrid reconfigurable parasitic antenna arrays

A parasitic reconfigurable antenna array is a low-power approach for beamforming using passive tunable elements. Prior work on reconfigurable antennas in communication theory is based on ideal radiation pattern abstractions. It does not address the problem of physical realizability. Beamforming with parasitic elements is inherently difficult because mutual coupling creates non-linearity in the beamforming gain objective. We develop a multi-port circuit-theoretic model of the hybrid array with parasitic elements and antennas with active RF chain validated through electromagnetic simulations with a dipole array. We then derive the beamforming weight of the parasitic element using the theoretical beam pattern expression for the case of a single active antenna and multiple parasitic elements. We show that the parasitic beamforming is challenging because the weights are subject to coupled magnitude and phase constraints. We simplify the beamforming optimization problem using a shift-of-origin transformation to the typical unit-modulus beamforming weight. With this transformation, we derive a closed-form solution for the reconfigurable parasitic reactance. We generalize this solution to the multi-active multi-parasitic hybrid array operating in a multi-path channel. Our proposed hybrid architecture with parasitic elements outperforms conventional architectures in terms of energy efficiency.

Frequency-selective beamforming and single-shot beam training with dynamic metasurface antennas

Dynamic metasurface antennas (DMAs) beamform through low-powered components that enable reconfiguration of each radiating element. Previous research on a single-user multiple-input-single-output (MISO) system with a dynamic metasurface antenna at the transmitter has focused on maximizing the beamforming gain at a fixed operating frequency. The DMA, however, has a frequency-selective response that leads to magnitude degradation for frequencies away from the resonant frequency of each element. This causes reduction in beamforming gain if the DMA only operates at a fixed frequency. We exploit the frequency reconfigurability of the DMA to dynamically optimize both the operating frequency and the element configuration, maximizing the beamforming gain. We leverage this approach to develop a single-shot beam training procedure using a DMA sub-array architecture that estimates the receiver's angular direction with a single OFDM pilot signal. We evaluate the beamforming gain performance of the DMA array using the receiver's angular direction estimate obtained from beam training. Our results show that it is sufficient to use a limited number of resonant frequency states to do both beam training and beamforming instead of using an infinite resolution DMA beamformer.