G radio for millimeter-wave (mm-wave) and beyond-5G concepts at 0.1-1 THz can exploit angle and delay measurements for localization through an increased bandwidth and large antenna arrays, but they are limited in terms of blockage caused by obstacles. Reconfigurable intelligent surfaces (RISs) are seen as a transformative technology that can control the physical propagation environment in which they are embedded by passively reflecting radio waves in preferred directions and actively sensing this environment in receive and transmit modes. While such RISs have mainly been intended for communication purposes, they can provide great benefits in terms of performance, energy consumption, and cost for localization and mapping. These benefits as well as associated challenges are the main topics of this article. ApplicationsThe interaction between the digital and physical worlds relies on high-definition situational awareness, i.e., the ability of a device to determine its own location as well as that of objects and other devices in the operating environment. Applications include automated vehicles and robots, in general, as well as health care, highly immersive virtual and augmented reality, and new human-to-machine interfaces. Situational awareness can be achieved with a variety of technologies, depending on the application and requirements, including lidar, inertial measurement units, and cameras. Additional technologies include radio-based ones such as satellite positioning, radar, ultrawideband, cellular, and Wi-Fi. Such technologies are attractive because they can have dual communication and sensing functionalities and are often less susceptible to environmental factors, such as poor lighting.Since 4G, dedicated localization reference signals have been considered part of communications system design and standardization. These can enable location accuracy levels on the order of 10 m. With 5G, the use of larger bandwidths and higher carrier frequencies, in combination with antenna arrays in user equipment (UE) and base stations (BSs), is expected to further improve location accuracy to roughly 1 m. Within beyond-5G systems, the trend is to operate at much higher frequencies

Channel estimation (CE) plays a key role in reconfigurable intelligent surface (RIS)-aided multipleinput multiple-output (MIMO) communication systems, while it poses a challenging task due to the passive nature of RIS and the cascaded channel structures. In this paper, a partially decoupled atomic norm minimization (PDANM) framework is proposed for CE of RIS-aided MIMO systems, which exploits the three-dimensional angular sparsity of the channel. In particular, PDANM partially decouples the differential angles at the RIS from other angles at the base station and user equipment, reducing the computational complexity compared with existing methods. A reweighted PDANM (RPDANM) algorithm is proposed to further improve CE accuracy, which iteratively refines CE through a specifically designed reweighing strategy. Building upon RPDANM, we propose an iterative approach named RPDANM with adaptive phase control (RPDANM-APC), which adaptively adjusts the RIS phases based on previously estimated channel parameters to facilitate CE, achieving superior CE accuracy while reducing training overhead. Numerical simulations demonstrate the superiority of our proposed approaches in terms of running time, CE accuracy, and training overhead. In particular, the RPDANM-APC approach can achieve higher CE accuracy than existing methods within less than 40 percent training overhead while reducing the running time by tens of times.

Millimeter-wave (mmWave) multiple-input multipleoutput (MIMO) system for the fifth generation (5G) cellular communications can also enable single-anchor positioning and object tracking due to its large bandwidth and inherently high angular resolution. In this paper, we introduce the newly invented concept, large intelligent surface (LIS), to mmWave positioning systems, study the theoretical performance bounds (i.e., Cramér-Rao lower bounds) for positioning, and evaluate the impact of the number of LIS elements and the value of phase shifters on the position estimation accuracy compared to the conventional scheme with one direct link and one non-line-of-sight path. It is verified that better performance can be achieved with a LIS from the theoretical analyses and numerical study.

The concept of reconfigurable intelligent surface (RIS) has been proposed to change the propagation of electromagnetic waves, e.g., reflection, diffraction, and refraction. To accomplish this goal, the phase values of the discrete RIS units need to be optimized. In this paper, we consider RISaided millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems for both accurate positioning and high datarate transmission. We propose an adaptive phase shifter design based on hierarchical codebooks and feedback from the mobile station (MS). The benefit of the scheme lies in that the RIS does not require deployment of any active sensors and baseband processing units. During the update process of phase shifters, the combining vector at the MS is also sequentially refined. Simulation results show the performance improvement of the proposed algorithm over the random design scheme, in terms of both positioning accuracy and data rate. Moreover, the performance converges to exhaustive search scheme even in the low signal-to-noise ratio regime.

Abstract-We consider channel/subspace tracking systems for temporally correlated millimeter wave (e.g., E-band) multipleinput multiple-output (MIMO) channels. Our focus is given to the tracking algorithm in the non-line-of-sight (NLoS) environment, where the transmitter and the receiver are equipped with hybrid analog/digital precoder and combiner, respectively. In the absence of straightforward time-correlated channel model in the millimeter wave MIMO literature, we present a temporal MIMO channel evolution model for NLoS millimeter wave scenarios. Considering that conventional MIMO channel tracking algorithms in microwave bands are not directly applicable, we propose a new channel tracking technique based on sequentially updating the precoder and combiner. Numerical results demonstrate the superior channel tracking ability of the proposed technique over independent sounding approach in the presented channel model and the spatial channel model (SCM) adopted in 3GPP specification.