RIS-Enabled Spoofing Against Adversary Sensing: CRB-Maximizing Design and Decoying Analysis

This paper studies the capability of a Reconfigurable Intelligent Surface (RIS), when transparently covering a User Equipment (UE), to deceive an adversary monostatic radar system. A compact RIS kernel model that explicitly links the radar's angular response to the RIS phase profile is introduced, enabling an analytical investigation of the Angle of Arrival (AoA) estimation accuracy with respect to the kernel's power. This model is also leveraged to formulate an RIS-based spoofing design with the dual objective to enforce strict nulls around the UE's true reflection AoA and maximize the channel gain towards a decoy direction. The RIS's deception capability is quantified using point-wise and angle-range robust criteria, and a configuration-independent placement score guiding decoy selection is proposed. Selected numerical results confirm deep nulls at the true reflection AoA together with a pronounced decoy peak, rendering maximum-likelihood sensing at the adversary radar unreliable.

RIS-Enabled Smart Wireless Environments: Fundamentals and Distributed Optimization

This chapter overviews the concept of Smart Wireless Environments (SWEs) motivated by the emerging technology of Reconfigurable Intelligent Surfaces (RISs). The operating principles and state-of-the-art hardware architectures of programmable metasurfaces are first introduced. Subsequently, key performance objectives and use cases of RIS-enabled SWEs, including spectral and energy efficiency, physical-layer security, integrated sensing and communications, as well as the emerging paradigm of over-the-air computing, are discussed. Focusing on the recent trend of Beyond-Diagonal (BD) RISs, two distributed designs of respective SWEs are presented. The first deals with a multi-user Multiple-Input Single-Output (MISO) system operating within the area of influence of a SWE comprising multiple BD-RISs. A hybrid distributed and fusion machine learning framework based on multi-branch attention-based convolutional Neural Networks (NNs), NN parameter sharing, and neuroevolutionary training is presented, which enables online mapping of channel realizations to the BD-RIS configurations as well as the multi-user transmit precoder. Performance evaluation results showcase that the distributedly optimized RIS-enabled SWE achieves near-optimal sum-rate performance with low online computational complexity. The second design focuses on the wideband interference MISO broadcast channel, where each base station exclusively controls one BD-RIS to serve its assigned group of users. A cooperative optimization framework that jointly designs the base station transmit precoders as well as the tunable capacitances and switch matrices of all metasurfaces is presented. Numerical results demonstrating the superior sum-rate performance of the designed RIS-enabled SWE for multi-cell MISO networks over benchmark schemes, considering non-cooperative configuration and conventional diagonal metasurfaces, are presented.

2D Waveguide-Fed Metasurface Antenna Arrays: Modeling and Optimization for Bistatic Sensing

This paper presents a physics-consistent framework for bistatic sensing incorporating a 2-Dimensional (2D) waveguide-fed metasurface antenna array capable of realizing eXtremely-Large Multiple-Input Multiple-Output (XL MIMO) apertures. A coupled-dipole model is presented that captures the array's mutual coupling due to both waveguide and free-space interactions, and a novel passivity constraint on the corresponding magnetic polarizabilities is proposed. Focusing on a bistatic sensing setup, we leverage a Neumann-series approximation of the array response model and derive the Cramer-Rao bound for multi-target parameter estimation, which is then incorporated into a sensing optimization formulation with respect to the metasurface's per-element resonance strength configuration. Simulation results on the position error bound in the radiative near field with the proposed design quantify the critical role of metamaterial placement in strongly coupled metasurface-based XL MIMO bistatic sensing systems.

Hybrid RISs for Simultaneous Tunable Reflections and Sensing

The concept of smart wireless environments envisions dynamic programmable propagation of information-bearing signals through the deployment of Reconfigurable Intelligent Surfaces (RISs). Typical RIS implementations include metasurfaces with passive unit elements capable to reflect their incident waves in controllable ways. However, this solely reflective operation induces significant challenges in the RIS orchestration from the wireless network. For example, channel estimation, which is essential for coherent RIS-empowered wireless communications, is quite challenging with the available solely reflecting RIS designs. This chapter 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, most importantly, giving rise to computationally autonomous and self-configuring RISs. The implementation details of HRISs are first presented, which are then followed by a convenient mathematical model for characterizing their dual functionality. Then, two indicative applications of HRISs are discussed, one for simultaneous communications and sensing and another that showcases their usefulness for estimating the individual channels in the uplink of a multi-user HRIS-empowered communication system. For both of these applications, performance evaluation results are included validating the role of HRISs for sensing as well as integrated sensing and communications.

Communications-Centric Secure ISAC with Hybrid Reconfigurable Intelligent Surfaces

Hybrid reconfigurable intelligent surfaces (HRISs) constitute an emerging paradigm of metasurfaces that empowers the concept of smart wireless environments, inherently supporting simultaneously communications and sensing. Very recently, some preliminary HRIS designs for Integrated Sensing And Communications (ISAC) have appeared, however, secure ISAC schemes are still lacking. In this paper, we present a novel communications-centric secure ISAC framework capitalizing on the dual-functional capability of HRISs to realize bistatic sensing simultaneously with secure downlink communications. In particular, we jointly optimize the BS precoding vector and the HRIS reflection and analog combining configurations to enable simultaneous accurate estimation of both a legitimate user and an eavesdropper, while guaranteeing a predefined threshold for the secrecy spectral efficiency, with both operations focused within an area of interest. The presented simulation results validate the effectiveness of the proposed secure ISAC design, highlighting the interplay among key system design parameters as well as quantifying the trade-offs between the HRIS's absorption and reflection coeffcients.

Tracking-Aided Multi-User MIMO Communications with Hybrid Reconfigurable Intelligent Surfaces

Hybrid Reconfigurable Intelligent Surfaces (HRISs) constitute a new paradigm that redefines smart metasurfaces, not only offering tunable reflections of incoming signals, but also incorporating signal reception and processing capabilities. In this paper, leveraging the simultaneous dual-functionality of HRISs, we propose a novel framework for tracking-aided multi-user Multiple-Input Multiple-Output (MIMO) communications. In particular, a joint design of the transmit multi-user precoding matrix together with the HRIS reflection and analog combining configurations is presented, with the objective to maximize the accuracy of position estimation of multiple mobile users while meeting their individual quality-of-service constraints for sensing-aided communications. The Cramer-Rao bound for the users' positioning parameters is derived together with a prediction approach based on the extended Kalman filter. Our simulation results showcase the efficacy of the proposed Integrated Sensing And Communications (ISAC) framework over various system configuration parameters.

DMA Reception for Simultaneous Area-Wide Sensing and Multi-User Uplink Communications

The recent surge in deploying extremely large antenna arrays is expected to play a vital role in future sixth generation wireless networks, enabling advanced radar target localization with enhanced angular and range resolution. This paper focuses on the promising technology of Dynamic Metasurface Antennas (DMAs), integrating numerous sub-wavelength-spaced metamaterials within a single aperture, and presents a novel framework for designing its analog reception beamforming weights with the goal to optimize sensing performance within a spatial Area of Interest (AoI), while simultaneously guaranteeing desired multi-user uplink communication performance. We derive the Cramer-Rao Bound (CRB) with DMA-based reception for both passive and active radar targets lying inside the AoI, which is then used as the optimization objective for configuring the discrete tunable phases of the metamaterials. Capitalizing on the DMA partially-connected architecture, we formulate the design problem as convex optimization and present both direct CRB minimization approaches and low complexity alternatives using a lower-bound approximation. Simulation results across various scenarios validate the effectiveness of the proposed framework, showing it consistently outperforms existing state-of-the-art methods.

Circuit-Compliant Optimization of Dynamic Metasurface Antennas for Near-Field Localization

This paper presents an optimization framework for near-field localization with Dynamic Metasurface Antenna (DMA) receivers. This metasurface technology offers enhanced angular and range resolution realizing efficient hybrid Analog and Digital (A/D) BeamForming (BF) with sub-wavelength-spaced metamaterials of tunable responses. However, the vast majority of the state-of-the-art DMA designs is based on an idealized model for their reception operation, which neglects several practical aspects, such as the inevitable mutual coupling among the densely deployed metamaterials within a given aperture. Capitalizing on a recent circuit-compliant active metasurface model, we present a novel mutual-coupling-aware framework for localization-optimized hybrid A/D BF weights at the reception DMA. To deal with the intrinsic complexity of the deployed model, we introduce first- and second-order approximations for the DMA analog BF matrix that enable efficient optimization, while maintaining accuracy. We derive the Cramer-Rao Bound for the user position estimation which serves as our design objective for the hybrid A/D BF matrices. Closed-form solutions for these matrices for both approximations are presented, whose validity is confirmed via numerical investigations. It is also demonstrated that the proposed DMA design outperforms state-of-the-art multi-antenna reception architectures optimized for the same localization objective.

Simultaneous Communications and Sensing with Hybrid Reconfigurable Intelligent Surfaces

Hybrid Reconfigurable Intelligent Surfaces (HRISs) constitute a new paradigm of truly smart metasurfaces with the additional features of signal reception and processing, which have been primarily considered for channel estimation and self-reconfiguration. In this paper, leveraging the simultaneous tunable reflection and signal absorption functionality of HRIS elements, we present a novel framework for the joint design of transmit beamforming and the HRIS parameters with the goal to maximize downlink communications, while simultaneously illuminating an area of interest for guaranteed localization coverage performance. Our simulation results verify the effectiveness of the proposed scheme and showcase the interplay of the various system parameters on the achievable Integrated Sensing and Communications (ISAC) performance.

Simultaneous Near-Field THz Communications and Sensing with Full Duplex Metasurface Transceivers

In this paper, a Full Duplex (FD) eXtremely Large (XL) Multiple-Input Multiple-Output (MIMO) node equipped with reconfigurable metasurface antennas at its transmission and reception sides is considered, which is optimized for simultaneous multi-user communications and sensing in the near-field regime at THz frequencies. We first present a novel Position Error Bound (PEB) analysis for the spatial parameters of multiple targets in the vicinity of the FD node, via the received backscattered data signals, and devise an optimization framework for its metasurface-based precoder and combiner. Then, we formulate and solve an optimization problem aiming at the downlink sum-rate maximization, while simultaneously ensuring a minimum PEB requirement for targets' localization. Our simulation results for a sub-THz system setup validate the joint near-field communications and sensing capability of the proposed FD XL MIMO scheme with metasurfaces antennas, showcasing the interplay of its various design parameters.