This letter introduces a reconfigurable intelligent surface (RIS)-assisted modulation scheme tailored for non-coherent receivers. Employing a RIS of dual-polarized elements, we manipulate the polarization state of the reflected signals to enable a differential polarization shift keying modulation scheme while simultaneously beamforming the reflected signal towards the receiver. Subsequently, an additional differential phase shift keying (DPSK) modulation layer is superimposed under two distinct deployments, where either the source or the RIS performs the DPSK modulation. Furthermore, the analytical performance is investigated, and a comparison with benchmark schemes is evaluated.

Polarization is a fundamental property of electromagnetic radio signals but often neglected in localization studies. In this paper, we study the potential benefits of integrating the polarization dimension into localization applications. We develop a three-dimensional (3D) geometric channel model between a base station (BS) and user equipment (UE), both equipped with dual-polarized (DP) antennas, which offers fundamental insights into the angles of departure (AoD) from the BS to the UE as well as the 3D orientation of the UE. From the model, we identify the degrees of freedom (DoF) provided by the polarization dimension for localization solutions by evaluating the rank of the equivalent Fisher information matrix. Subsequently, we leverage these DoF to introduce three distinct localization applications: (i) 3D orientation estimation, (ii) 2D AoD estimation, and (iii) mixed 2D position and 1D orientation estimation for vehicular scenarios. Furthermore, for the three localization applications we identify their regions of operation in terms of the ranges of the angles of interest, to avoid any ambiguity occurrence through the estimation process, thereby guaranteeing unique solutions. Finally, we derive the Cramér-Rao lower bounds and numerically establish the efficiency of the proposed estimators.

We propose a joint polarization and spatial modulation (JPSM) scheme using reconfigurable intelligent surface (RIS). In this scheme, a RIS equipped with dual-polarized (DP) reflecting elements is used to assist the communication between a transmitter of a single polarized antenna and a receiver equipped with a uniform linear array of DP antennas, while additionally encoding the reflected waves on the RIS to perform JPSM scheme. The information data is encoded in terms of the receiver DP antenna index as well as the polarization state of the received signal. Furthermore, we develop exhaustive and heuristic RIS phase shift design solutions to enable the RIS-JPSM scheme. Moreover, both an optimum maximum likelihood and a low complexity greedy detectors are formulated. The proposed scheme enhances the data rate by operating higher-order polarization modulation in comparison to the conventional RIS-based spatial modulation scheme.

Reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for 6G networks. In this study, we explore a novel use case for RIS: passive localization and tracking of a RIS-equipped object using monostatic sensing, where the fixed transmitter and receiver share the same single antenna, using OFDM signals. We develop a low-complexity algorithm that achieves centimeter-level accuracy using only 6 MHz bandwidth, and by applying temporal coding to random RIS phase profiles, separating signals from undesired multipath sources. In addition, we evaluate the impact of model uncertainty on the performance of the algorithm.

Single antenna sensors in the rapidly emerging Internet-of- Things (IoT) are attractive due to their simplicity and low cost. However, determining their own positions autonomously using only a single antenna is challenging. This paper presents a novel approach for autonomous downlink localization of single-antenna receivers using Reconfigurable Intelligent Surfaces (RIS) and a tracking process using the complex extended Kalman filter (EKF). Simulation results show that the considered RIS-aided wireless radio system can provide accurate localization and continuous fast tracking down to the centimeter level, especially when multiple RISs are deployed. Furthermore, various factors affecting the system performance are analyzed in detail.

We propose a novel binary polarization shift keying modulation scheme for a line-of-sight environment by exploiting the polarization control ability of the reconfigurable intelligent surface (RIS). The RIS encodes the information data in terms of the polarization states of either the reflected wave from the RIS or the composite wireless channel between an RF source and receiver. In the first case, polarization mismatch correction becomes essential at the receiver. In the second case, the RIS pre-codes the reflected wave to compensate for the polarization mismatch which allows non-coherent demodulation at the receiver.

We propose a novel reconfigurable intelligent surface (RIS)-aided differential polarization shift keying modulation scheme for a line-of-sight environment. In this scheme, the RIS exploits the state of polarization (SoP) of the reflected waves over two successive reflection frames to encode the data bit. In particular, the RIS either preserves the SoP of the reflected wave similar to the previous reflection frame or switches it to another orthogonal SoP as a function of the information data bits. The proposed scheme allows non-coherent data detection without the need for polarization mismatch estimation and compensation processes at the receiver.    

Estimation of a radio receiver's location from single-antenna observations - the received signal strength - is well known for its limited accuracy and lack of robustness. Yet, for reasons of energy- and space efficiency, emerging IoT devices will often be equipped with a single antenna. In this paper, we show how reconfigurable intelligent surfaces (RISs) can bring robustness and precision to this estimation problem. We propose a novel RIS-assisted SISO location scheme, based on new dynamic RIS reconfiguration protocols and an associated Maximum Like-lihood location estimation. We derive the Fisher information, the Cramér- Rao bound, and evaluate through simulations the effects of various relative RIS geometries and RIS reconfiguration pro-tocols. Our results indicate that the deployment of multiple RISs in the far-field allows for centimeter-level estimator accuracy. Reconfiguring RISs in a (pseudo-) random manner outperforms a deterministic orderly protocol by about 4 dB.

In line-of-sight (LoS) environments, point-to-point (P2P) multiple-input multiple-output (MIMO) channel matrix turns out to be rank deficient such that spatial multiplexing becomes unattainable. In this paper, we propose the deployment of distributed intelligent reflecting surfaces (IRSs) to act as artificial scatterers and synthesize a sort of multi-path propagation such that additional degrees of freedom are created. We show that given the far-field deployment of the IRS, it simply resembles a full-duplex relay with a single effective reflection coefficient. However, to maximize the channel capacity both the effective reflection coefficients of all IRSs and the transmit covariance matrix should be jointly optimized, which is a nonconvex optimization problem. Thus, we develop an alternating optimization algorithm to iteratively find a sub-optimal solution. Moreover, we propose different schemes to enhance the composite channel power which would result in an improvement to the achievable rate. Our simulation results show that the deployment of distributed IRSs with P2P MIMO systems in LoS environments increases the rank of the channel matrix, and improves the achievable rate by making spatial multiplexing possible.