Next-generation cellular networks will witness the creation of smart radio environments (SREs), where walls and objects can be coated with reconfigurable intelligent surfaces (RISs) to strengthen the communication and localization coverage by controlling the reflected multipath. In fact, RISs have been recently introduced not only to overcome communication blockages due to obstacles but also for high-precision localization of mobile users in GPS denied environments, e.g., indoors. Towards this vision, this paper presents the localization performance limits for communication scenarios where a single next generation NodeB base station (gNB), equipped with multiple-antennas, infers the position and the orientation of a user equipment (UE) in a RIS-assisted SRE. We consider a signal model that is valid also for near-field propagation conditions, as the usually adopted far-field assumption does not always hold, especially for large RISs. For the considered scenario, we derive the Cramer-Rao lower bound (CRLB) for assessing the ultimate localization and orientation performance of synchronous and asynchronous signaling schemes. In addition, we propose a closed-form RIS phase profile that well suits joint communication and localization, and we perform extensive numerical results to assess the performance of our scheme for various localization scenarios and for various RIS phase design. Numerical results show that the proposed scheme can achieve remarkable performance, even in asynchronous signaling and that the proposed phase design approaches the numerical optimal phase design that minimizes the CRLB.

This paper considers a scenario where a reconfigurable intelligent surface (RIS) is deployed to allow the localization of mobile users adopting a single anchor node, even under non-line-of-sight (NLOS) channel conditions. When the RIS is large and the operating frequency is high, as in the millimeter-wave band, the system is likely to operate in the near-field propagation regime, which can be exploited to obtain robust localization. To this purpose, two practical signaling and positioning algorithms, based on an orthogonal frequency division multiplexing (OFDM) downlink system, are proposed along with methods to design the RIS time-varying reflection coefficients. In the numerical results, the two algorithms are compared in terms of performance in the presence of a synchronization mismatch and considering trade-offs between bandwidth, overhead, operating frequency, and latency. Finally, we provide an analysis of the soft-coverage capability, i.e., on the possibility of maintaining a high level of localization accuracy when in the presence of increasing levels of obstruction of the RIS.

Applications towards 6G have brought a huge interest towards arrays with a high number of antennas and operating within the millimeter and sub-THz bandwidths for joint communication, sensing, and localization. With such large arrays, the plane wave approximation is often not accurate because the system may operate in the (radiating) near-field propagation region (i.e., the Fresnel region) where the electromagnetic field wavefront is spherical. In this case, the curvature of arrival (CoA) is a measure of the spherical wavefront that can be used to infer the source position using only a single large antenna array. In this paper, we study a near-field tracking problem for inferring the state (i.e., the position and velocity) of a moving source with an ad-hoc observation model that accounts for the phase-difference profile of a large receiving array. For this tracking problem, we derive the posterior Cramer-Rao Lower Bound (P-CRLB) to show the effects when the source moves inside and outside the Fresnel region. We provide insights on how the loss of positioning information outside Fresnel results from an increase of the ranging error rather than from inaccuracies of angular estimation. Then, we investigate the accuracy and complexity performance of different Bayesian tracking algorithms in the presence of model parameter mismatches and abrupt trajectory changes. Our results demonstrate the feasibility and high accuracy of most tracking approaches without the need for wideband signals and of any synchronization scheme.

In next generation of cellular networks, it is desirable to use single access points both for communication and localization. This could be made possible thanks to the combination of femtocells, mm-wave communications and massive antenna arrays and would overcome the problem of having an over-sized infrastructure for positioning which is, nowadays, the bottleneck for the widespread diffusion of indoor localization systems. In this context, our paper aims at investigating the localization and orientation performance limits employing massive arrays both at the access point (AP) and mobile side. To this end, we first asymptotically demonstrate the tightness of the Cramér- Rao bound (CRB) in the massive array regime and that the effect of multipath can be made negligible even for practical values of SNR levels. Successively, we propose a comparison between two different transmitter configurations, namely MIMO where orthogonal waveforms are sent, and beamforming, which takes advantage of highly correlated waveforms and directive array patterns. We also consider random weighting as a trade-off between the diversity gain of MIMO and the high directivity guaranteed by the beamforming. CRB results show the interplay between diversity and beamforming gain as well as the benefits achievable by varying the number of antennas in terms of localization accuracy and multipath mitigation.

The adoption of millimeter-wave technology could open the possibility to integrate massive antenna arrays inside future 5G user mobile devices, with the possibility to enable new interesting applications. Within this context, in this paper we put forth the concept of a personal mobile radar operating at millimeter-waves and consisting of a massive array for accurate environmental mapping. Frequency selectivity and phase quantization effects are accounted for to characterize the achievable angle and range resolution necessary to collect environmental information. Successively, we propose an effective grid-based Bayesian mapping approach by introducing a new state-space model, which profits of the beneficial effects of the massive antenna array characteristics. Numerical results show that the idea herein investigated is feasible, and that a significant mapping performance is attainable even employing coarse antenna arrays provided that the number of antenna elements is sufficiently high.

Next generation cellular networks will experience the combination of femtocells, millimeter-wave (mmW) communications and massive antenna arrays. In addition to benefits in terms of an increased communication capacity, this mix of technologies can be fruitfully exploited to enable high-accuracy indoor positioning. In fact, thanks to the high beamforming capability of massive arrays, mobile terminal localization can be performed in principle by using only one single access point (AP), thus avoiding costly infrastructures with additional APs dedicated to positioning. In this context, our paper aims at investigating the localization and orientation performance limits of networks employing wideband massive arrays both at receiving and transmitting devices. In particular, the effects of the array structure, bandwidth and synchronization error are studied both at mmW and at 10GHz, when phased, timed and random arrays are employed.