Large antenna arrays and high-frequency bands are two key features of future wireless communication systems. The combination of large-scale antennas with high transmission frequencies often results in the communicating devices operating in the near-field (Fresnel) region. In this paper, we study the potential of beam focusing, feasible in near-field operation, in facilitating high-rate multi-user downlink multiple-input multiple-output (MIMO) systems. As the ability to achieve beam focusing is dictated by the transmit antenna, we study near-field signalling considering different antenna structures, including fully-digital architectures, hybrid phase shifter-based precoders, and the emerging dynamic metasurface antenna (DMA) architecture for massive MIMO arrays. We first provide a mathematical model to characterize near-field wireless channels as well as the transmission pattern for the considered antenna architectures. Then, we formulate the beam focusing problem for the goal of maximizing the achievable sum-rate in multi-user networks. We propose efficient solutions based on the sum-rate maximization task for fully-digital, (phase shifters based-) hybrid and DMA architectures. Simulation results show the feasibility of the proposed beam focusing scheme for both single- and multi-user scenarios. In particular, the designed focused beams provide a new degree of freedom to mitigate interference in both angle and distance domains, which is not achievable using conventional far-field beam steering, allowing reliable communications for uses even residing at the same angular direction.

We demonstrate a low-profile holographic imaging system at millimeter wavelengths based on an aperture composed of frequency-diverse metasurfaces. Utilizing measurements of spatially-diverse field patterns, diffraction-limited images of human-sized subjects are reconstructed. The system is driven by a single microwave source swept over a band of frequencies (17.5–26.5 GHz) and switched between a collection of transmit and receive metasurface panels. High fidelity image reconstruction requires a precise model for each field pattern generated by the aperture, as well as the manner in which the field scatters from objects in the scene. This constraint makes scaling of computational imaging systems inherently challenging for electrically large, coherent apertures. To meet the demanding requirements, we introduce computational methods and calibration approaches that enable rapid and accurate imaging performance.

This article covers recent advances in the fusion of metasurface antenna design and computational imaging concepts for the realization of imaging systems that are planar, fast, and low cost. We start by explaining the operation of metamaterial antennas which can generate diverse radiation patterns. Their advantages and distinctions from previous antennas are elucidated. We then provide an intuitive overview of the computational imaging framework and argue that metamaterial antennas are a near ideal platform for implementing such schemes at microwave frequencies. We describe two metamaterial antenna implementations: frequency-diverse and electronically reconfigurable. The trade-offs governing the design and operation of each architecture are examined. We conclude by examining the outlook of metamaterial antennas for microwave imaging and propose various future directions.

Massive multiple-input multiple-output (MIMO) communications are the focus of considerable interest in recent years. While the theoretical gains of massive MIMO have been established, implementing MIMO systems with large-scale antenna arrays in practice is challenging. Among the practical challenges associated with massive MIMO systems are increased cost, power consumption, and physical size. In this work we study the implementation of massive MIMO antenna arrays using dynamic metasurface antennas (DMAs), an emerging technology which inherently handles the aforementioned challenges. Specifically, DMAs realize large-scale planar antenna arrays, and can adaptively incorporate signal processing methods such as compression and analog combining in the physical antenna structure, thus reducing the cost and power consumption. We first propose a mathematical model for massive MIMO systems with DMAs and discuss their constraints compared to ideal antenna arrays. Then, we characterize the fundamental limits of uplink communications with the resulting systems, and propose two algorithms for designing practical DMAs for approaching these limits. Our numerical results indicate that the proposed approaches result in practical massive MIMO systems whose performance is comparable to that achievable with ideal antenna arrays. Index terms— Massive MIMO, metasurfaces, antenna design.

The latest discussions on upcoming 6G wireless communications are envisioning future networks as a unified communications, sensing, and computing platform. The recently conceived concept of the smart radio environment, enabled by reconfigurable intelligent surfaces (RISs), contributes toward this vision, offering programmable propagation of information-bearing signals. Typical RIS implementations include metasurfaces with almost passive unit elements capable of reflecting their incident waves in controllable ways. However, this solely reflective operation induces significant challenges for RIS optimization from the wireless network orchestrator. For example, RISs lack information to locally tune their reflection pattern, which can be acquired only by other network entities and then shared with the RIS controller. Furthermore, channel estimation, which is essential for coherent RIS-empowered communications, is challenging with the available RIS designs. This article reviews the emerging concept of hybrid reflecting and sensing RISs (HRISs), which enables metasurfaces to reflect the impinging signal in a controllable manner while simultaneously sensing a portion of it. The sensing capability of HRISs facilitates various network management functionalities, including channel parameter estimation and localization, while giving rise to potentially computationally autonomous and self-configuring metasurfaces. We discuss a hardware design for HRISs and detail a full-wave electromagnetic (EM) proof of concept. The distinctive properties of HRISs, in comparison to their solely reflective counterparts, are highlighted, and a simulation study evaluating HRISs’ capability for performing full and parametric channel estimation is presented. Future research challenges and opportunities arising from the HRIS concept are also included.

We present a dynamic metamaterial aperture for use in computational imaging schemes at microwave frequencies. The aperture consists of an array of complementary, resonant metamaterial elements patterned into the upper conductor of a microstrip line. Each metamaterial element contains two diodes connected to an external control circuit such that the resonance of the metamaterial element can be damped by application of a bias voltage. Through applying different voltages to the control circuit, select subsets of the elements can be switched on to create unique radiation patterns that illuminate the scene. Spatial information of an imaging domain can thus be encoded onto this set of radiation patterns, or measurements, which can be processed to reconstruct the targets in the scene using compressive sensing algorithms. We discuss the design and operation of a metamaterial imaging system and demonstrate reconstructed images with a 10:1 compression ratio. Dynamic metamaterial apertures can potentially be of benefit in microwave or millimeter wave systems such as those used in security screening and through-wall imaging. In addition, feature-specific or adaptive imaging can be facilitated through the use of the dynamic aperture.