Simulation Platform for Wireless Sensor Networks Based on Impulse Radio Ultra Wide Band

Impulse Radio Ultra Wide Band (IR-UWB) is a promising technology to address Wireless Sensor Network (WSN) constraints. However, existing network simulation tools do not provide a complete WSN simulation architecture, with the IR-UWB specificities at the PHYsical (PHY) and the Medium Access Control (MAC) layers. In this paper, we propose a WSN simulation architecture based on the IR-UWB technique. At the PHY layer, we take into account the pulse collision by dealing with the pulse propagation delay. We also modelled MAC protocols specific to IRUWB, for WSN applications. To completely fit the WSN simulation requirements, we propose a generic and reusable sensor and sensing channel model. Most of the WSN application performances can be evaluated thanks to the proposed simulation architecture. The proposed models are implemented on a scalable and well known network simulator: Global Mobile Information System Simulator (GloMoSim). However, they can be reused for all other packet based simulation platforms

Simulation of Multi-element Antenna Systems for Navigation Applications

The application of user terminals with multiple antenna inputs for use with the global satellite navigation systems like GPS and Galileo becomes more and more attraction in last years. Multiple antennas may be spread over the user platform and provide signals required for the platform attitude estimation or may be arranged in an antenna array to be used together with array processing algorithms for improving signal reception, e.g. for multipath and interference mitigation. In order to generate signals for testing of receivers with multiple antenna inputs and corresponding receiver algorithms in a laboratory environment a unique HW signal simulation tool for wavefront simulation has been developed. The signals for a number of antenna elements in a flexible user defined geometry are first generated as digital signals in baseband and then mixed up to individual RF-outputs. The paper describes the principle function of the system and addresses some calibration issues. Measurement set-ups and results of data processing with simulated signals for different applications are shown and discussed

Penetration Depth of a Soil Moisture Profile Probe Working in Time-Domain Transmission Mode

Soil moisture is one of the most important soil parameters. Knowledge of volumetric water content (VWC) of the root zone as well as the VWC dynamics in the soil profile is especially important for agriculture. Monitoring VWC at several depths in the soil profile can be performed using several soil moisture sensors placed at various depths. However, the use of a profile probe is more convenient, because the installation of a single probe is less disturbing to the soil, as well as less laborious and more cost-effective. The objective of the paper is to present the design and performance of a novel profile probe working in the time-domain transmission mode (P-TDT probe) with emphasis put on the penetration depth and sensitivity zone. The performance of the probe was assessed with the use of finite element method (FEM) simulations in the frequency domain, transient simulations in the time domain and laboratory experiments with the use of a vector network analyzer (VNA) working in the 10 MHz–10 GHz frequency range. It was concluded that the effective soil volume measured by the profile probe of a given geometry is equivalent to a soil thickness of about 20 mm around the tested probe. The internal part of the probe body had a negligible effect on the measurement results, as it does not change with soil moisture. Moreover, the transmitted signal amplitude was related to the soil electrical conductivity

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results