Sigint Solutions



Project Name: WHERE - Wireless Hybric Enchanced Mobile Radio Estimators

Research Programme: EU Seventh Framework Programme, Information and Communication Technologies

EC Instrument: STREP Project

Call: FP7-ICT-2007-1

Contract Number: 217033

Man-Power Effort: 529 Person-Months

Total Financial Volume 5.551 Million Euro

EC Funding 4.047 Million Euro

Duration 30 months (01.01.2008 – 30.06.2010)


  • German Aerospace Center (DLR),Institute of Communications and Navigation, Germany (Coordinator)
  • Aalborg University (Denmark)
  • Advanced Communications Research&Development S.A. (Spain)
  • Commissariat à L’Energie Atomique – LETI (France)
  • Institut Eurécom (France)
  • Siradel (France)
  • Université de Rennes 1 (France)
  • Instituto Telecomunicações (Portugal)
  • Mitsubishi Electric ITE (France)
  • Sigint Solutions Ltd. (CYPRUS)
  • University of Surrey (UK)
  • Universidad Politécnica de Madrid (Spain)
  • University of Alberta (Canada)
  • City University of Hong Kong (Hong Kong)


Description of work

The main objective of WHERE is to combine wireless communications and navigation for the benefit of future mobile radio systems. The impact will be manifold, such as real time localization knowledge in B3G/4G systems which increase the cellular capacity. GPS as well as the upcoming European Satellite Navigation System Galileo will be supplemented with techniques that improve accuracy and availability of indoor navigation and location based service coverage.
To enable ubiquitous mobile network access and to increase data rates, scientific and technological development is more and more focusing on the integration of radio access networks (RANs). This allows an efficient use even if the radio access technology behind such networks is dynamically changing. The knowledge of the position of mobile terminals is for an efficient usage of RANs valuable information in order to allocate resources or even to predict the allocation within a heterogeneous RAN infrastructure.
The hybrid system approach addressed in the WHERE project encompasses key innovations beyond state of the art for both communications and positioning. A joint consideration of both aspects will allow exploiting synergies among them. In the field of communications, key innovations of WHERE are:
  • Communication using multiple RANs or radio access technologies (RATs); optimization of that heterogeneous communications infrastructure based on positioning information of base stations and possibly RAN nodes. Examples of such RAT combinations could be cellular/WiFi or cellular/P2P. Location based protocols, developed and investigated in WHERE, enable such heterogeneous network connectivity even if the availability of different RANs/RATs is dynamic. This leads to a more efficient use of the available radio resources through advanced location based radio resource management and handover algorithms.
  • On the physical layer (PHY) technologies and procedures, which take into account positioning information, are researched. Such approaches optimize MIMO strategies (spatial multiplexing, spatial diversity) or provide adaptive macro diversity techniques.
The motivation for providing accurate position estimation is twofold: Positioning information is provided also in scenarios, which are critical for global navigation satellite system (GNSS) based navigation. On the other side an operation of location-based RAN technologies with independency to GNSS is achieved.
Sigints Description of Work (Research work, experiments, papers, documentation, demos, results : It should include images/snapshots/photos/videos and text.
In WHERE, Sigint has contributed at the physical layer with localisation/positioning activities based on 3D channel modeling. More specifically, Sigint has contributed to the channel modeling section by providing radio channel predictions through its 3D Ray Tracing Simulator (3DTruEM) for the purpose of implementing and testing positioning algorithms. The full deterministic engine of the simulator and its ability to incorporate a detailed geometry and morphology of the environment together with its built-in antenna designer allows the estimation of realistic channel predictions. These predictions include Received Signal Strength (RSS), Angular information such as Angle of Arrival (AoA) and Angle of Departure (AoD), Power Delay Profiles (PDP) and Channel Impulse Response (CIR).

3DTruEM Simulator
In order to increase the accuracy and get robust operational propagation predictions from Ray Tracing model, it is necessary to perform a calibration of some specific input parameters to the model. The fundamental and easiest way to carry out calibration is to use coverage or PDP measurements of the scenario under investigation and try to match those to the Ray Tracing prediction while at the same time modifying the input parameters to the model. Geometrical information can be provided with high accuracy (e.g. through 3D DXF files etc), but very accurate electromagnetic properties are not easily available. The exact knowledge of the electric permittivity and the loss tangent of every wall or facet in a wireless environment require extensive on-site measurements of every facet (S11 and/or S21), which makes the whole process very impractical and very time consuming. The aim is to try to calibrate the ray tracing model to be more accurate for the environment under investigation. It is therefore important to calibrate the electromagnetic parameters (relative permittivity and loss tangent) of the reflecting walls in the given environment. In this context Sigint has calibrated its Ray Tracing Simulator (3DTruEM) for a specific indoor wireless environment where narrowband measurements where performed by modeling the exact geometry of the environment through 3DTruEM CAD designer.

Environment to be calibrated

Modeled Environment

Starting from typical electrical parameters given in literature, an iterative calibration algorithm was used to tune these electrical parameters in order to minimize the error in the Power Delay Delay. The following figures show typical examples of this calibration process.

Calibration Example 1 Calibration Example 2

Sigint has also developed a Ray Tracing-based fingerprinting positioning algorithm and has investigated effect on its positioning accuracy with regards to uncertainties about the modeled environment geometry and morphology.

The basic idea behind channel-based fingerprinting is to store the pre-calculated or pre-measured position depended signal information (e.g. Received Signal Strength Indication –RSSI, Power Delay Profile – PDP etc) – known as ‘fingerprints’ or position signatures – for the entire coverage area of the cellular system in a database and then try to match or correlate a measured signal to the ones stored in the database. It is common practice to generate these fingerprinting databases through an extensive measurement campaign, however this is very laborious and takes time. Therefore Ray Tracing sounds like a better option. Ray Tracing accuracy is therefore strictly related to the accuracy its input parameters. For this reason, various environment/profile parameter uncertainties were introduced and their effect on the received power delay profile (PDP) was investigated through the use of 3DTruEM. These parameter uncertainties include variations in the geometric description of the scenario in terms of location and size of the obstructions, variations in the morphology of the walls, introduction of low-level stationary clutter (e.g. cars, furniture etc) and uncertainties in the antenna radiation pattern. The latter can be introduced due to the various orientations that the mobile user would hold his/her terminal.

Typical example of the effect of low stationary clutter on the PDP
In this work some basic uncertainties that most likely would exist when simulating an outdoor scenario have been investigated. These uncertainties concern the morphology and geometry of the obstructions/buildings and also the location and radiation pattern of the transmitting antennas. They have significant impact on the accuracy of the fingerprints (Impulse Responses) to be simulated using Ray Tracing and stored into the database for positioning purposes. A Manhattan-like outdoor scenario has been used for this investigation where typical UMTS network topology was assumed and the Impulse Responses have been calculated using 3DTruEM. This topology consists of both micro and macro base stations. The results have indicated that the investigated uncertainties caused the following errors on the predicted Impulse Response (IR):

Typical root mean squared error (RMSE) on the PDP due to various environment uncertainties


WHERE Broshure