A general non-asymptotic theoretical analysis is developed for fingerprinting localization system designs. Based on this analysis, hybrid fingerprinting and propagation-based methods are proposed using 5G-like received signal strength (RSS), time of arrival (TOA), and direction of arrival (DOA) measurements which have been a focus in recent 3GPP Rel 16 and Rel 17 positioning activities. The proposed hybrid methods have the flexibility and robustness of fingerprinting methods in dealing with none-line-of-sight (NLOS) problem while inheriting the efficiency and accuracy of propagation-based methods in 3-D localization. Specifically, a ray extension technique is developed as the propagation-based method. Then the ray extension is combined with two fingerprinting methods, the conventional weighted k-nearest neighbors (WKNN) and the proposed optimal WKNN (OWKNN), in order to remedy the geometrical deficiency in fingerprinting methods. Based on the non-asymptotic study, the proposed hybrid methods are guaranteed to outperform the fingerprinting methods without ray extension. Verification of the proposed methods is performed in a large none-line-of-sight (NLOS) urban San Jose region using simulation data provided by a previously developed super-efficient ray launcher.

In this work, the Discrete, Environment-Driven Ray Launching (DED-RL) algorithm, which makes use of parallelization on Graphic Processing Units, fully described in a previous paper, has been validated versus a large set of measurements to evaluate its performance in terms of both computational efficiency and accuracy. Three major urban areas have been considered, including a very challenging scenario in central San Francisco that was used as a benchmark to test an image-ray tracing algorithm in a previous work. Results show that DED-RL is as accurate as ray tracing, despite the much lower computation time, reduced by more than three orders of magnitude with respect to ray tracing. Moreover, the accuracy level only marginally depends on discretization pixel size, at least for the considered pixel size range. The unprecedented computational efficiency of DED-RL opens the way to numerous applications, ranging from RF coverage optimization of drone-aided cellular networks to efficient fingerprinting localization applications, as briefly discussed in the paper.

This paper proposes a novel framework for analyzing the localization accuracy of data fusion for fingerprinting approaches in non-line-of-sight (NLOS) environments. Using simulation data generated for two very different NLOS environments (a suburban area of $3.3km\times 3.3km$ in Santa Clara, California, and a mountainous area of $11.4km\times 11.4km$ in the Caspian region), we establish novel channel models for measurement differences of three data types (received signal strength indicator (RSS), time of arrival (TOA) and direction of arrival (DOA)) at $K$ neighboring nodes of an arbitrary node. The crucial point is that the modeling errors for each of the three data types are shown to be jointly Gaussian distributed. Based on these measurement difference models, Cramer-Rao Lower Bound (CRLB) is used as a benchmark to evaluate $K$ -nearest neighbor (KNN) and Weighted $K$ -Nearest Neighbor (WKNN). It is shown that the proposed CRLB analyses can be employed to evaluate fingerprinting systems with various designs (such as different data types and fusion options) and different configurations (such as densities of reference nodes and numbers of anchor nodes) in diverse NLOS environments(such as suburban and mountainous regions).

Interaction of UHF radio waves with a typical office building and the resulting scattering characteristics are studied in this communication using millimeter-wave frequency measurements and ray-tracing simulations on a scale model of the building. A "disaggregation approach" is followed to separately test different structural elements (facade, internal structure, furniture) and to separately simulate different interaction mechanisms (specular reflection, edge diffraction, transmission, diffuse scattering) thus achieving a deeper understanding of the propagation process. Results suggest that scattering from buildings can be modeled neglecting the internal structure of the building, but proper modeling of nonspecular propagation is necessary, even with a controlled and completely known environment such as the scale building model.

Interaction of UHF radio waves with a typical office building and the resulting scattering characteristics are studied in this communication using millimeter-wave frequency measurements and ray-tracing simulations on a scale model of the building. A “disaggregation approach” is followed to separately test different structural elements (facade, internal structure, furniture) and to separately simulate different interaction mechanisms (specular reflection, edge diffraction, transmission, diffuse scattering) thus achieving a deeper understanding of the propagation process. Results suggest that scattering from buildings can be modeled neglecting the internal structure of the building, but proper modeling of nonspecular propagation is necessary, even with a controlled and completely known environment such as the scale building model.

Localization schemes based on direction of arrival (DOA) in none-line-of-sight (NLOS) environments are developed. The proposed kernel-based machine learning method is innovative and can provide accurate position estimation under none-line-of sight (NLOS) conditions. The proposed kernel-based method is compared with the Weighted K-nearest neighborhood (WKNN) fingerprinting method using simulated DOA data in practical rural environment. It shows that the kernel-based method gives more accurate localization results.

A fully discrete Ray Launching field prediction algorithm that takes advantage of environment visibility preprocessing for both diffuse and specular interactions is presented and used to perform efficient RF coverage prediction in large environments. The algorithm, being discrete, has been parallelized in a straightforward way on NVIDIA-compatible Graphical Processing Units. These innovative features combined allow to achieve a computation time reduction of about three orders of magnitude compared to conventional algorithms, while retaining the same accuracy level.

We present here a novel, fully discrete ray launching field prediction algorithm that takes advantage of environment preprocessing to efficiently trace rays undergoing both specular and diffuse interactions. The algorithm is “environment driven” because rays are traced from the ray source according to the presence and distribution of obstacles in the surrounding space, therefore adapting ray density to the environment’s characteristics. The environment is discretized into simple regular shapes to facilitate faster geometric computations, to allow for visibility preprocessing and for the algorithm to be parallelized in a straightforward way. These innovative features combined together and implemented on a NVIDIA graphical processing unit (GPU) are shown to speed-up computation by several orders of magnitude compared to more conventional algorithms, while retaining a similar accuracy level. The speed-up and prediction accuracy achieved in reference cases is presented in comparison with a pre-existing ray-based model and RF-coverage measurements.

A robust kernel-based machine learning localization scheme using time of arrival (TOA) or time difference of arrival (TDOA) in none-line-of-sight (NLOS) environments is proposed. The scheme can provide accurate position estimation while the reference nodes are coarsely and randomly distributed in the area of interests. Moreover, the scheme is insensitive with respect to random TOA synchronization and measurement errors.

This paper presents an extension of the ITU-R P.1411-8 urban low antenna path loss models to higher antennas. The Line-of-Sight (LOS) and non-Line-of-Sight (NLOS) urban canyon models presented in the paper are typically used for street level peer-to peer or cellular communications, but can be more generally used to account for radio waves propagating through urban street canyons. It is shown through comparisons with measurements of varying transmit antenna height and large variations of height difference between transmit and receive antennas, that the presented urban street canyon models are applicable to taller microcellular antennas. The measurements that are used in the comparisons and analysis were obtained in an urban high-rise environment in San Francisco at 850 and 1920 MHz frequencies.

The prediction of indoor coverage from outdoor base stations should be of even greater interest than outdoor prediction, as most wireless data traffic is generated indoors. Due to difficulties in acquiring indoor building maps on a large scale and integrating outdoor and indoor propagation models, outdoor-to-indoor prediction has been limited in practice to the use of generic outdoor-to-indoor attenuation factors or empirical formulas. In the present work, we propose a hybrid method based on deterministic 3-D outdoor prediction on building surfaces and indoor extension using a radiosity-based iterative method that does not require a detailed building map. Prediction results are checked against measurements and, surprisingly, they appear to be almost as accurate as outdoor prediction results.

The prediction of cellular RF coverage at street level in urban environment has been addressed in many studies in the past two decades. Nevertheless, the prediction of indoor coverage on upper floors, much less popular within the scientific community, is of even greater interest, as most of the traffic of outdoor cellular base stations actually comes from indoor users.

In this paper, line-of-sight (LOS) and non-line-of-sight (NLOS) models of the small-area average received power are presented for microcellular radio links. These computationally efficient models consider the propagation loss incurred by path loss and shadow fading through urban street canyons. The models are validated with microcellular measurements recorded at 850 and 1900 MHz in San Francisco. Comparisons are also performed with the Cost-231-Walfisch-Ikegami model and show the importance of including urban canyon contributions in microcellular propagation prediction.

The prediction of RF coverage in urban environments is now commonly considered a solved problem with tens of models proposed in the literature showing good performance against measurements. Among these, ray tracing is regarded as one of the most accurate ones available. In the present work, however, we show that a great deal of work is still needed to make ray tracing really unleash its potential in practical use. A very extensive validation of a state-of-the-art 3D ray tracing model is carried out through comparison with measurements in one of the most challenging environments: the city of San Francisco. Although the comparison is based on RF cellular coverage at 850 and 1900 MHz, a widely studied territory, very relevant sources of error and inaccuracy are identified in several cases along with possible solutions.

Back-scattering from buildings at 2GHz is studied through measurements on a 60 GHz scaled-model and ray tracing simulations. Comparing simulations to measurements, which separately consider different interaction mechanisms (reflection, diffraction, and diffuse scattering), we validate our ray tracing model and determine the relative importance of each interaction mechanism to the back-scattered signal.

In this work, a 60 GHz empirical investigation on a scale model is performed to give insight into building scattering at 2 GHz. From the presented building scattering measurements, the relative effects of the furniture and building surface on the building scattered signal are determined. The fading statistics of the scattered signal are also determined and are found to be Rayleigh distributed. Lastly, a simple method to compute the scattered power from a building using the effective roughness approach is presented and validated using the measurements.

This work investigates the propagation characteristics of an office building in the 60 GHz band. From reflection and scattering measurements of several painted and un-painted common building materials recorded at 60 GHz, the complex permittivity and Lambert's Law scattering coefficient of each material are extracted. Diffraction measurements from two building corners at 60 GHz are also presented and analyzed. Lastly, power angular profiles of building penetration and scattering at 60 GHz are presented and used to characterize the outdoor to indoor propagation, and the significant scatterers on a building surface, respectively.

This paper presents site-specific models for the real-time prediction of the received power from waves propagating through urban street canyons (i.e., in the horizontal plane containing the transmitter and receiver) for radio communication in urban environments. The line-of-sight (LOS) and non-line-of-sight (NLOS) models presented here are based on the two-ray model and are used to predict the small-area average received power (i.e., long-term/shadow fading and distance-dependence). These models have two adjustable parameters that account for clutter such as road traffic and pedestrians, and for scattering from objects and buildings at street intersections, respectively. Validation of these models is performed with mobile-to-mobile measurements recorded in the high-rise sections of Denver and New York City for frequencies ranging from 430 MHz to 4.86 GHz.

This paper investigates diffracted and scattered waves in unlicensed millimeter wave mobile-to-mobile, access and backhaul radio links. Narrowband 60 GHz measurements of diffraction at building corners, and scattering by a car, lamppost and building, as well as blocking by humans are presented. Semi-analytical corner diffraction and human blocking models are proposed and verified based on the measurements. Analysis of the diffraction and scattering shows that the contributions from vehicular and lamppost scattered paths can be dominant compared to corner diffracted paths. Measurements also show that the majority of power from building scattering arrives in and near the horizontal plane containing the transmit and receive antennas.

In this work, we investigate building scattering at 2 GHz by performing 60 GHz scattering measurements on a 1/30 scale building model. The materials used to build this model were chosen to have similar reflected and transmitted power characteristics at 60 GHz to common building materials at 2 GHz. Co-polarized and cross-polarized scattering measurements of the model were performed with and without furniture and the front building surface. Near the specular direction, results show that the contribution from waves that enter a building, internally scatter and/or reflect, and then exit the building are not significant compared to those that only interact with the features on the front building surface. However, away from the specular direction, this contribution can be observed.