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The technology of reconfigurable intelligent surfaces (RISs) has been showing promising potential in a variety of applications relying on Beyond-5G networks. RIS can indeed provide fine channel flexibility to improve communication quality of service (QoS) or restore localization capabilities in challenging operating conditions, while conventional approaches fail (e.g., due to insufficient infrastructure, severe radio obstructions). In this paper, we tackle a general low-complexity approach for optimizing the precoders that control such reflective surfaces under hardware constraints. More specifically, it allows the approximation of any desired beam pattern using a pre-characterized lookup table of feasible complex reflection coefficients for each RIS element. The proposed method is first evaluated in terms of beam fidelity for several examples of RIS hardware prototypes. Then, by means of a theoretical bounds analysis, we examine the impact of RIS beams approximation on the performance of near-field downlink positioning in non-line-of-sight conditions, while considering several RIS phase profiles (including directional, random and localization-optimal designs). Simulation results in a canonical scenario illustrate how the introduced RIS profile optimization scheme can reliably produce the desired RIS beams under realistic hardware limitations. They also highlight its sensitivity to both the underlying hardware characteristics and the required beam kinds in relation to the specificity of RIS-aided localization applications. [ABSTRACT FROM AUTHOR]

Among the key differentiators of 6G compared to 5G will be the increased emphasis on radio-based positioning and sensing. These will be utilized not only for conventional location-aware services and for enhancing communication performance but also to support new use case families with extreme performance requirements. This article presents a unified vision from stakeholders across the value chain in terms of both opportunities and challenges for 6G positioning and sensing as well as use cases, performance requirements, and gap analysis. Combined, this motivates the technical advances in 6G and guides system design. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) have attracted enormous interest thanks to their ability to overcome line-of-sight blockages in mmWave systems, enabling in turn accurate localization with minimal infrastructure. Less investigated are however the benefits of exploiting RIS with suitably designed beamforming strategies for optimized localization and synchronization performance. In this paper, a novel low-complexity method for joint localization and synchronization based on an optimized design of the base station (BS) active precoding and RIS passive phase profiles is proposed, for the challenging case of a single-antenna receiver. The theoretical position error bound is first derived and used as metric to jointly optimize the BS-RIS beamforming, assuming a priori knowledge of the user position. By exploiting the low-dimensional structure of the solution, a novel codebook-based robust design strategy with optimized beam power allocation is then proposed, which provides low-complexity while taking into account the uncertainty on the user position. Finally, a reduced-complexity maximum-likelihood based estimation procedure is devised to jointly recover the user position and the synchronization offset. Extensive numerical analysis shows that the proposed joint BS-RIS beamforming scheme provides enhanced localization and synchronization performance compared to existing solutions, with the proposed estimator attaining the theoretical bounds even at low signal-to-noise-ratio and in the presence of additional uncontrollable multipath propagation. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is a promising technological enabler for the 6th generation (6G) of wireless systems with applications in localization and communication. In this paper, we consider the problem of positioning a single-antenna user in 3D space based on the received signal from a single-antenna base station and reflected signal from an RIS by taking into account the mobility of the user and spatial-wideband (WB) effects. To do so, we first derive the spatial-WB channel model under the far-field assumption, for orthogonal frequency-division multiplexing signal transmission with the user having a constant velocity. We derive the Cramér Rao bounds to serve as a benchmark. Furthermore, we devise a low-complexity estimator that attains the bounds in high signal-to-noise ratios. Our estimator neglects the spatial-WB effects and deals with the user mobility by estimating the radial velocities and compensating for their effects in an iterative fashion. We show that the spatial-WB effects can degrade the localization accuracy for large RIS sizes and large signal bandwidths as the direction of arrival or departure deviate from the RIS normal. In particular, for a 64 × 64 RIS, the proposed estimator is resilient against the spatial-WB effects up to 140 MHz bandwidth. Regarding user mobility, our results suggest that the velocity of the user influences neither the bounds nor the accuracy of our estimator. Specifically, we observe that the state of the user with a high speed (42 m/s) can be estimated virtually with the same accuracy as a static user. [ABSTRACT FROM AUTHOR]

Distributed MIMO (D-MIMO) with synchronized access points (APs) is a promising architecture for both communications and localization in 5G and beyond systems. In this letter, we develop a time-difference-of-arrival (TDOA)-based indoor localization system using a 2.35-GHz high-speed sigma-delta-over-fiber (SDoF) D-MIMO testbed with 40-MHz bandwidth, exploiting the fully synchronized nature of the APs. Experimental results over an area of size 100 m2 demonstrate accuracies below 0.2 m and agree with the theoretical Cramér–Rao bounds (CRBs) at most measurement locations, indicating the localization capability of high-speed SDoF D-MIMO. [ABSTRACT FROM AUTHOR]

We consider the problem of spatial signal design for multipath-assisted mmWave positioning under limited prior knowledge on the user’s location and clock bias. We propose an optimal robust design and, based on the low-dimensional precoder structure under perfect prior knowledge, a codebook-based heuristic design with optimized beam power allocation. Through numerical results, we characterize different position-error-bound (PEB) regimes with respect to clock bias uncertainty and show that the proposed low-complexity codebook-based designs outperform the conventional directional beam codebook and achieve near-optimal PEB performance for both analog and digital architectures. [ABSTRACT FROM AUTHOR]

Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at mm-wave and sub-THz bands. In this article, we address the radio-based sensing and environment mapping prospects with specific emphasis on the user equipment (UE) side. We first describe an efficient $\ell _1$ -regularized least-squares (LS) approach to obtain sparse range–angle charts at individual measurement or sensing locations. For the subsequent environment mapping, we then introduce a novel state model for mapping diffuse and specular scattering, which allows efficient tracking of individual scatterers over time using interacting multiple model (IMM) extended Kalman filter and smoother. Also the related measurement selection and data association problems are addressed. We provide extensive numerical indoor mapping results at the 28 GHz band deploying OFDM-based 5G NR uplink waveform with 400 MHz channel bandwidth, covering both accurate ray-tracing based as well as actual RF measurement results. The results illustrate the superiority of the dynamic tracking-based solutions, compared to static reference methods, while overall demonstrate the excellent prospects of radio-based mobile environment sensing and mapping in future mm-wave networks. [ABSTRACT FROM AUTHOR]

Intercarrier interference (ICI) poses a significant challenge for OFDM joint radar-communications (JRC) systems in high-mobility scenarios. In this paper, we propose a novel ICI-aware sensing algorithm for MIMO-OFDM JRC systems to detect the presence of multiple targets and estimate their delay-Doppler-angle parameters. First, leveraging the observation that spatial covariance matrix is independent of target delays and Dopplers, we perform angle estimation via the MUSIC algorithm. For each estimated angle, we next formulate the radar delay-Doppler estimation as a joint carrier frequency offset (CFO) and channel estimation problem via an APES (amplitude and phase estimation) spatial filtering approach by transforming the delay-Doppler parameterized radar channel into an unstructured form. To account for the presence of multiple targets at a given angle, we devise an iterative interference cancellation based orthogonal matching pursuit (OMP) procedure, where at each iteration the generalized likelihood ratio test (GLRT) detector is employed to form decision statistics, providing as by-products the maximum likelihood estimates (MLEs) of radar channels and CFOs. In the final step, target detection is performed in delay-Doppler domain using target-specific, ICI-decontaminated channel estimates over time and frequency, where CFO estimates are utilized to resolve Doppler ambiguities, thereby turning ICI from foe to friend. The proposed algorithm can further exploit the ICI effect to introduce an additional dimension (namely, CFO) for target resolvability, which enables resolving targets located at the same delay-Doppler-angle cell. Simulation results illustrate the ICI exploitation capability of the proposed approach and showcase its superior detection and estimation performance in high-mobility scenarios over conventional methods. [ABSTRACT FROM AUTHOR]

This article presents a shared vision among stakeholders across the value chain on the use of radio positioning and sensing for road safety in the 5G ecosystem. The key enabling technologies and architectural functionalities are explored, focusing on the extremely stringent localization and communication requirements. A case study for joint radar and communication using experimental data showcases the potential of the new enablers that are paving the way toward enhanced road safety in beyond 5G scenarios. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are set to be a revolutionary technology in the 6th generation of wireless systems. In this work, we study the application of RIS in a multi-user passive localization scenario, where we have one transmitter (TX) and multiple asynchronous receivers (RXs) with known locations. Classical approaches fail in this scenario due to lack of synchronization and lack of data association between multi-static measurements and users. To resolve this, we consider each user to be equipped with an RIS, and show that we can avoid the data association problem and estimate users’ 3D position with submeter accuracy in a large area around the transmitter, using time-of-arrival measurements at the RXs. We develop a low-complexity estimator that attains the corresponding Cramér-Rao bound as well as a novel RIS phase profile design to remove inter-path interference. [ABSTRACT FROM AUTHOR]

In the automotive sector, both radars and wireless communication are susceptible to interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate interference in both systems. This article analyses the mutual interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of interference among FMCW based automotive radars, including self-interference, using radar and communication cooperation. The results show that RadChat can significantly reduce radar mutual interference in single-hop vehicular networks in less than 80 ms. [ABSTRACT FROM AUTHOR]

The problem of minimizing total power consumption in light-emitting diode transmitters is investigated for achieving power efficient localization in a visible light communication and positioning system. A robust power allocation approach based on stochastic uncertainties is proposed for total power minimization in the presence of localization accuracy, power, and illumination constraints. Specifically, the power consumption minimization problem is formulated under a chance constraint on the probability of Cramér–Rao lower bound exceeding a tolerable limit, which is a computationally intractable constraint. The sphere bounding method is used to propose a safe convex approximation to this intractable constraint, which makes the resulting problem suitable for standard convex optimization tools. Numerical results demonstrate the advantages of the proposed robust solution over the nonrobust solution and uniform power allocation in the presence of stochastic uncertainty. [ABSTRACT FROM AUTHOR]

Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyzes automotive radar interference and proposes several new approaches that combine industrial and academic expertise toward the goal of achieving interference-free autonomous driving (AD). [ABSTRACT FROM AUTHOR]

The problem of optimal power allocation among light emitting diode (LED) transmitters in a visible light positioning system is considered for the purpose of improving localization performance of visible light communication (VLC) receivers. Specifically, the aim is to minimize the Cramér-Rao lower bound (CRLB) on the localization error of a VLC receiver by optimizing LED transmission powers in the presence of practical constraints, such as individual and total power limitations and illuminance constraints. The formulated optimization problem is shown to be convex and thus can efficiently be solved via standard tools. We also investigate the case of imperfect knowledge of localization parameters and develop robust power allocation algorithms by taking into account both overall system uncertainty and individual parameter uncertainties related to the location and orientation of the VLC receiver. In addition, we address the total power minimization problem under predefined accuracy requirements to obtain the most energy-efficient power allocation vector for a given CRLB level. Numerical results illustrate the improvements in localization performance achieved by employing the proposed optimal and robust power allocation strategies over the conventional uniform and non-robust approaches. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) is an emerging paradigm that enables multiple functionalities to be accomplished concurrently, including illumination, high-speed data communications, and localization. Based on the VLC technology, visible light positioning (VLP) systems aim to estimate locations of VLC receivers by utilizing light-emitting diode (LED) transmitters at known locations. VLP presents a viable alternative to radio frequency (RF)-based positioning systems by providing inexpensive and accurate localization services. In this paper, we consider the problem of localization in visible light systems and provide an extensive survey of various location estimation techniques, accompanied by discussions of their relative merits and demerits within the context of accuracy and computational complexity. In addition, we investigate a cooperative VLP system architecture in which VLC receiver units are able to communicate with each other for the purpose of cooperation, and present a low-complexity, iterative localization algorithm to demonstrate the benefits of cooperation in VLP systems. Finally, we investigate optimal strategies for power allocation among LED transmitters to maximize the localization accuracy subject to power and illumination constraints. [ABSTRACT FROM AUTHOR]

Visible light positioning (VLP) systems based on light emitting diodes can facilitate high accuracy localization services for indoor scenarios. In this paper, direct and two-step positioning approaches are investigated for both synchronous and asynchronous VLP systems. First, the Cramér–Rao lower bound (CRLB) and the direct positioning-based maximum likelihood estimator are derived for 3-D localization of a visible light communication receiver in a synchronous scenario by utilizing information from both time delay parameters and channel attenuation factors. Then, a two-step position estimator is designed for synchronous VLP systems by exploiting the asymptotic properties of time-of-arrival and received signal strength estimates. The proposed two-step estimator is shown to be asymptotically optimal, i.e., converges to the direct estimator at high signal-to-noise ratios. In addition, the CRLB and the direct and two-step estimators are obtained for positioning in asynchronous VLP systems. It is proved that the two-step position estimation is optimal in asynchronous VLP systems for practical pulse shapes. Various numerical examples are provided to illustrate the improved performance of the proposed estimators with respect to the current state-of-the-art and to investigate their robustness against model uncertainties in VLP systems. [ABSTRACT FROM PUBLISHER]

In this paper, optimal power allocation strategies are investigated for jammer nodes in a wireless localization system. Building upon the concept of the restricted Bayesian approach, a generalized optimization strategy, called the restricted scheme, is proposed for power allocation of jammer nodes, and its theoretical properties are characterized. In the restricted scheme, the aim is to maximize the average Cramer-Rao lower bound (CRLB) of target nodes while keeping their minimum CRLB above a predefined level in the presence of average (total) and peak power constraints. It is proved that the average CRLB achieved by the restricted scheme is a strictly decreasing and concave function of the constraint on the minimum CRLB level. A closed-form solution is obtained for the restricted scheme when the tradeoff parameter and the total power limit are below certain thresholds. In addition, it is shown that the optimal solution of the restricted scheme corresponds to the use of at most NT jammer nodes, where NT is the number of target nodes, and that the optimal solution of the minimum CRLB maximization scheme is determined by at most NJ target nodes, where NJ is the number of jammer nodes. Extensions of the restricted scheme and an alternative scheme that aims to maximize the number of disabled target nodes (whose CRLBs are above a preset level) are considered, and the corresponding optimal strategies for jammer power allocation are identified. Numerical examples are provided to verify the theoretical derivations for various network configurations. [ABSTRACT FROM AUTHOR]

In this study, the Ziv–Zakai bound (ZZB) is derived for synchronous visible light positioning (VLP) systems. The proposed ZZB extracts ranging information from the prior information, the time delay parameter, and the channel attenuation factor based on the Lambertian pattern. In addition to the ZZB, the Bayesian Cramér–Rao bound (CRB) and the weighted CRB (WCRB) are calculated for synchronous VLP systems. Furthermore, a closed-form expression is obtained for the expectation of the conditional CRB (ECRB). Numerical examples are presented to compare the bounds against each other and against the maximum a posteriori probability (MAP) estimator. It is observed that the ZZB can provide a reasonable lower limit on the performance of MAP estimators. On the other hand, the WCRB and the ECRB converge to the ZZB in regions of low and high source optical powers, respectively; however, they are not tight in other regions. [ABSTRACT FROM PUBLISHER]

In this paper, theoretical limits and estimators are studied for synchronous and asynchronous visible light positioning (VLP) systems. Specifically, the Cramér–Rao lower bounds (CRLBs) and maximum likelihood estimators are investigated for distance estimation based on time-of-arrival (TOA) and/or received signal strength (RSS) parameters. Hybrid TOA/RSS-based distance estimation is proposed for VLP systems, and its CRLB is compared analytically against the CRLBs of TOA-based and RSS-based distance estimation. In addition, to investigate the effects of sampling, asymptotic performance results are obtained under sampling rate limitations as the noise variance converges to zero. A modified hybrid TOA/RSS-based distance estimator is proposed to provide performance improvements in the presence of sampling rate limitations. Numerical examples are presented to illustrate the theoretical results. [ABSTRACT FROM PUBLISHER]