An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters

A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values

Multipath-assisted maximum-likelihood indoor positioning using UWB signals

Multipath-assisted indoor positioning (using ultrawideband signals) exploits the geometric information contained in deterministic multipath components. With the help of a-priori available floorplan information, robust localization can be achieved, even in absence of a line-of-sight connection between anchor and agent. In a recent work, the Cramér-Rao lower bound has been derived for the position estimation variance using a channel model which explicitly takes into account diffuse multipath as a stochastic noise process in addition to the deterministic multipath components. In this paper, we adapt this model for position estimation via a measurement likelihood function and evaluate the performance for real channel measurements. Performance results confirm the applicability of this approach. A position accuracy better than 2.5 cm has been obtained in 90% of the estimates using only one active anchor at a bandwidth of 2GHz and robustness against non-line-of-sight situations has been demonstrated

Intelligent Reflecting Surfaces Positioning in 6G Networks

The work analyzed the positioning of IRS over the coverage region of micro cell to derive optimal placement location to support cell-edge Internet of Things (IoT) devices with a favorable signal-to-interference plus noise ratio (SINR). Moreover, the work derived that the implementation of IRS significantly enhances energy efficiency notably reducing the transmit power of the micro cell base station

A Graph-based Algorithm for Robust Sequential Localization Exploiting Multipath for Obstructed-LOS-Bias Mitigation

This paper presents a factor graph formulation and particle-based sum-product algorithm (SPA) for robust sequential localization in multipath-prone environments. The proposed algorithm jointly performs data association, sequential estimation of a mobile agent position, and adapts all relevant model parameters. We derive a novel non-uniform false alarm (FA) model that captures the delay and amplitude statistics of the multipath radio channel. This model enables the algorithm to indirectly exploit position-related information contained in the MPCs for the estimation of the agent position. Using simulated and real measurements, we demonstrate that the algorithm can provide high-accuracy position estimates even in fully obstructed line-of-sight (OLOS) situations, significantly outperforming the conventional amplitude-information probabilistic data association (AIPDA) filter. We show that the performance of our algorithm constantly attains the posterior Cramer-Rao lower bound (PCRLB), or even succeeds it, due to the additional information contained in the presented FA model.Comment: corrected small errors, changed titl

6G Enabled Advanced Transportation Systems

The 6th generation (6G) wireless communication network is envisaged to be able to change our lives drastically, including transportation. In this paper, two ways of interactions between 6G communication networks and transportation are introduced. With the new usage scenarios and capabilities 6G is going to support, passengers on all sorts of transportation systems will be able to get data more easily, even in the most remote areas on the planet. The quality of communication will also be improved significantly, thanks to the advanced capabilities of 6G. On top of providing seamless and ubiquitous connectivity to all forms of transportation, 6G will also transform the transportation systems to make them more intelligent, more efficient, and safer. Based on the latest research and standardization progresses, technical analysis on how 6G can empower advanced transportation systems are provided, as well as challenges and insights for a possible road ahead.Comment: Submitted to an open access journa

Design, simulation and experimental evaluation of indoor localization schemes for 60 GHz millimeter wave systems

This thesis targets localization schemes for single-anchor millimeter wave systems. The devised algorithms are evaluated by means of simulations in order to draw initial conclusions about their robustness. The obtained results are then validated via measurements involving commercial pre-standard 60-GHz MMW hardware, showing that by relying only on a single anchor, the algorithms can localize a node with high probability, and in many cases with sub-meter accurac