Radio Localization and Mapping With Reconfigurable Intelligent Surfaces: Challenges, Opportunities, and Research Directions

Abstract

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

Tensor-Based Algebraic Channel Estimation for Hybrid IRS-Assisted MIMO-OFDM

“…Moreover, these estimation uncertainties will undermine the integration of IRS in many wireless services. For example, the IRS-based modulation of [33] can only broadcast properly modulated symbols to the receivers after equalizing the distortion effects of the transmitter-IRS channel; the environment mapping of [34] manages to determine the object surfaces and scatter points based on exact measurements of the received signal strength (RSS), time of arrival (ToA) and angle of arrival/departure (AoA/AoD); the user localization and the mobility tracking of [35], [36] also require precise estimation of the propagation distance and azimuth/elevation angles from the MSs. Unfortunately, without any a priori information, the one-hop channels, as well as, the path parameters cannot be properly recovered from the cascaded channel estimation.…”

“…is a connected graph, ∀ℓ ∈ I(L), (34) with A x , A y defined as in (32), then the rank of Y equals L, and its CPD is unique up to scaling and permutation ambiguities.…”

Radiation Pattern Prediction for Metasurfaces: A Neural Network-Based Approach

“…Here, we elaborate upon the locally tunable scenario, which expands our incremental framework to a locally tunable MSF ( Figure 4 , Case 3). Such MSFs enable applications such as object tracking [ 19 , 20 , 21 ] and sensing [ 22 , 24 ]. Hence, they will be of significant importance in 6G networks.…”

“…Moreover, research efforts presenting experimental prototypes, such as [ 16 , 17 , 18 ], further provision insights into how the RISs can engineer the channel and demonstrate the feasibility of the RIS approach and its significant improvements for wireless communications in complex transmission environments. RISs also find their application in other use-cases such as the indoor geo-localization, which has been elaborated in [ 19 , 20 , 21 ]. Note that indoor geo-localization will be extremely critical for future networks as the use of mmWaves/THz band will necessitate detailed knowledge of the mobile device’s location for precise beamforming/beam-steering.…”

Assessing Wireless Sensing Potential With Large Intelligent Surfaces

“…The performance analysis of LIS and RIS assisted systems has attracted considerable attention in the recent years, and many works have studied the applicability of these technologies. For instance, the use of RIS to control the signals propagation has been analyzed in the context of communications through the so-called passive beamforming [7,[12][13][14], in location and positioning systems [15][16][17], and in physical layer This work was submitted for review on 18 th February 2021. A preliminary version of this work has been accepted to 15-th EAI International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM 2020) [1].…”