Distributed spectrum sensing in a cognitive networking testbed

In this demonstration, we show how the IBBT w-iLab.t wireless testbed, combined with multiple spectrum sensing engines designed by imec, can be used for experimentally-supported design and evaluation of cognitive networking protocols. Functionalities include the advanced characterization of the behavior of a cognitive solution under test, and characterization of the wireless experimentation environment itself

Spectrum sensing for cognitive wireless applications inside aircraft cabins

Wireless intra-aircraft communication is expected to be the enabler for more flexible avionic systems and the reduction of weight and cost in system installations. An alternative to the usage of a dedicated frequency band for wireless intra-aircraft avionics could be the usage of a virtually unregulated ISM band. Cognitive radio techniques could be used to increase system robustness in the likely case of interferences in this kind of frequency bands. A cognitive wireless cabin management system is discussed as a use-case for the validation of this approach. Using the mobile cognitive radio testbed of the FP7 project CREW, spectrum sensing experiments are carried out in a realistic aircraft cabin environment as a baseline for the development of suitable cognitive protocols and to record interference scenarios for the further system design

Spectrum sensing for cognitive wireless applications inside aircraft cabins

Wireless intra-aircraft communication is expected to be the enabler for more flexible avionic systems and the reduction of weight and cost in system installations. An alternative to the usage of a dedicated frequency band for wireless intra-aircraft avionics could be the usage of a virtually unregulated ISM band. Cognitive radio techniques could be used to increase system robustness in the likely case of interferences in this kind of frequency bands. A cognitive wireless cabin management system is discussed as a use-case for the validation of this approach. Using the mobile cognitive radio testbed of the FP7 project CREW, spectrum sensing experiments are carried out in a realistic aircraft cabin environment as a baseline for the development of suitable cognitive protocols and to record interference scenarios for the further system design

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling desig