Power-Based Direction-of-Arrival Estimation Using a Single Multi-Mode Antenna

Phased antenna arrays are widely used for direction-of-arrival (DoA) estimation. For low-cost applications, signal power or received signal strength indicator (RSSI) based approaches can be an alternative. However, they usually require multiple antennas, a single antenna that can be rotated, or switchable antenna beams. In this paper we show how a multi-mode antenna (MMA) can be used for power-based DoA estimation. Only a single MMA is needed and neither rotation nor switching of antenna beams is required. We derive an estimation scheme as well as theoretical bounds and validate them through simulations. It is found that power-based DoA estimation with an MMA is feasible and accurate

Optimized Waveform for Energy Efficient Ranging

Mobile communication terminals exploit existing reference signal structures for propagation delay based positioning. However, the used waveforms are not optimized for energy efficiency and improved ranging performance for positioning. Recently, a parametric waveform with adaptable power spectral density has been proposed in the context of 5G, and has shown an improved ranging performance. In this paper, we investigate the energy reduction of a ranging signal for a targeted ranging performance by adjusting the parametric waveform. We focus on the newly opened 28 GHz frequency band offering 850 MHz of contiguous bandwidth in the United States. Based on derived Ziv-Zakai lower bounds and a mmWave path loss model with shadow fading we determine the optimal waveform parameter. Our results show a transmit power reduction of 4.77 dB compared to existing reference signal structures. Furthermore, we show a link budget example in the context of ITS positioning

Modelling Aspects of Planar Multi-Mode Antennas for Direction-of-Arrival Estimation

Multi-mode antennas are an alternative to classical antenna arrays, and hence a promising emerging sensor technology for a vast variety of applications in the areas of array signal processing and digital communications. An unsolved problem is to describe the radiation pattern of multi-mode antennas in closed analytic form based on calibration measurements or on electromagnetic field (EMF) simulation data. As a solution, we investigate two modeling methods: One is based on the array interpolation technique (AIT), the other one on wavefield modeling (WM). Both methods are able to accurately interpolate quantized EMF data of a given multi-mode antenna, in our case a planar four-port antenna developed for the 6-8.5 GHz range. Since the modeling methods inherently depend on parameter sets, we investigate the influence of the parameter choice on the accuracy of both models. Furthermore, we evaluate the impact of modeling errors for coherent maximum-likelihood direction-of-arrival (DoA) estimation given different model parameters. Numerical results are presented for a single polarization component. Simulations reveal that the estimation bias introduced by model errors is subject to the chosen model parameters. Finally, we provide optimized sets of AIT and WM parameters for the multi-mode antenna under investigation. With these parameter sets, EMF data samples can be reproduced in interpolated form with high angular resolution

Exploring spatial diversity techniques for future broadband multicarrier mobile radio systems

Abstract — In this paper, we investigate broadband OFDM systems which apply beamforming in combination with different space–time diversity techniques. Various beamforming scenarios with transmitter and/or receiver sided beamforming are considered. Space–time diversity is obtained by cyclic delay diversity (CDD) in order to artificially shape the spectrum of the received signal. Thus, an advantageous distribution of the errors before a Viterbi channel decoder is obtained. Simulation results for the bit error rate performance are presented and compared for OFDM systems applying different beamforming scenarios and CDD in a Rayleigh fading channel. Maximum ratio combining (MRC) of the signals received on multiple beams/antennas and inter-carrierinterference (ICI) is also taken into account in the performance analysis. I

The 5G Localisation Waveform

Todays cellular networks have distinct services that come with different requirements, figures of merit, etc. for each application. A communication service such as voice communication relies on latency better than 150 ms and bit error rates lower than 1

Location-Aware Formation Control in Swarm Navigation

Goal-seeking and information-seeking are canonical problems in mobile agent swarms. We study the problem of collaborative goal-approaching under uncertain agent position information. We propose a framework that establishes location-aware formations, resulting in a controller that accounts for agent position uncertainty with a realistic ranging model. Simulation results confirm that, as the outcome of the controller, the swarm moves towards its goal, while emerging formations conducive to high-quality localization

Waveform Parameter Selection for ITS Positioning

In this paper, we investigate the performance of mobile vehicle positioning based on signal propagation delay estimation in the uplink case for a realistic propagation environment. In order to optimize the ranging performance, we introduce a parametric waveform. This waveform contains a scalar parameter for adjusting the distribution of the available signal power over the frequency. The optimization is achieved by a functional dependency between the waveform parameter and the positioning error. In order to derive a cost function, we combine the approaches of the Cramér-Rao and Ziv-Zakai bounds for position and propagation delay estimation. As an exemplary environment we consider a mobile vehicle located in an area surrounded by three base stations together with realistic propagation conditions provided by the WINNER II channel model. The results show that the waveform parameter has to be adjusted differently compared to a simple free space propagation scenario. Additionally, we compare the obtained results with a scenario with four base stations and a scenario where we use the WINNER II channel model in terms of line-of-sight received power and shadow fading to classify the effects of geometry and propagation conditions

Mixture Density Networks for Multipath Assisted Positioning-based Fingerprinting

In multipath assisted positioning schemes, the spatial information contained in multipath propagation of wireless radio systems is exploited for localization of a receiver. However, such schemes suffer from a high computational complexity. We have proposed before a fingerprinting localization system based on multipath assisted positioning, where the fingerprinting database is encoded in a deep neural network (DNN). Within this paper, we propose and evaluate a mixture density network approach in our DNN to analyze ambiguities among fingerprints at different locations. We show that our scheme shows a very good positioning performance with an error of around 2m for the most part, while having a low computational complexity in the online stage and a very low effort compared to traditional fingerprinting schemes

On the Positioning Performance of VDES R-Mode

Ships nowadays greatly rely on Global Navigation Satellite Systems (GNSSs) in order to deter- mine their position. Since GNSS outages or jamming events do occur, there are efforts to reduce the dependency on GNSS for maritime navigation. One such effort is called R-Mode (Ranging Mode), and focuses on complementing maritime communication systems by a ranging compo- nent to enable a vessel to determine its position. One of the systems to be extended by R-Mode is the VHF Data Exchange System (VDES). The VDES communication system is currently in standardization and offers 100 kHz of bandwidth in the maritime VHF band. It utilizes sin- gle carrier modulation with pi/4-QPSK. The proposed R-Mode extension works by sending a precisely timed known data sequence, so that time of arrival estimation allows determination of the range. Using software defined radios (SDR), we implemented a test setup for VDES R-Mode with three base stations on land and one receiver located on a vessel. Using this setup, we performed the first VDES R-Mode positioning trials on the Lake Ammer in Germany. By determining the time of the arrival as well as the Doppler shift of the received signals we tracked the vessels position with an Unscented Kalman Filter. The positioning accuracy performance ranged to up to 22 m under favourable conditions. Crucial was the consideration of the Doppler measurements to enhance tracking performance considerably

Entropy of Transmitter Maps in Cooperative Multipath Assisted Positioning

In multipath assisted positioning, multipath components (MPCs) are regarded as line-of-sight (LoS) signals from virtual transmitters. The locations of physical and virtual transmitters are typically unknown, but can be estimated jointly with the location of a mobile terminal using simultaneous localization and mapping (SLAM). When users cooperate by exchanging maps of estimated positions of physical and virtual transmitters, the positioning performance can be improved drastically. Within this paper, we investigate such transmitter maps that are shared among users. We derive an approximation of the entropy of transmitter maps that is based on the unscented transform and analyze the evolution of this entropy over time. Our simulations indicate that the transmitter maps converge quickly