A Belief-Based Decision-Making Framework for Spectrum Selection in Cognitive Radio Networks

This paper presents a comprehensive cognitive management framework for spectrum selection in cognitive radio (CR) networks. The framework uses a belief vector concept as a means to predict the interference affecting the different spectrum blocks (SBs) and relies on a smart analysis of the scenario dynamicity to properly determine an adequate observation strategy to balance the tradeoff between achievable performance and measurement requirements. In this respect, the paper shows that the interference dynamics in a given SB can be properly characterized through the second highest eigenvalue of the interference state transition matrix. Therefore, this indicator is retained in the proposed framework as a relevant parameter to drive the selection of both the observation strategy and spectrum selection decision-making criterion. This paper evaluates the proposed framework to illustrate the capability to properly choose among a set of possible observation strategies under different scenario conditions. Furthermore, a comparison against other state-of-the-art solutions is presented

On Demonstrating Spectrum Selection Functionality for Opportunistic Networks

This paper presents a testbed platform to demonstrate and validate spectrum opportunity identification and spectrum selection functionalities in Opportunistic Networks (ONs). The hardware component of the testbed is based on reconfigurable devices able to transmit and receive data at different operating frequencies, which are dynamically configured. The software component has been developed to perform the creation and maintenance of ON radio links, including spectrum opportunity identification and selection decision making as well as all the necessary signaling to support the ON operation. Therefore, the presented platform provides a powerful tool for testing different algorithms in real operational radio environments under various interference conditions, thus enabling to gain deeper insight into the performance of algorithmic solutions, beyond the purely theoretical analyses based on models and/or simulations. Results presented in the paper validate the implementation conducted at the laboratory and illustrate the reconfigurability capabilities of the ON links under different conditions

Validation platform implementation description - D5.2

This deliverable describes different test-beds for the validation of the architecture, algorithms and protocols for the operator governed opportunistic networking as defined in the OneFIT Project. Further on, this deliverable provides a description of the implementation of the OneFIT cognitive management systems CSCI and CMON as well as the C4MS protocol. Also, implementation of the blocks supporting the OneFIT system (JRRM, CCM, DSONPM, and DSM) is described. This document also describes the implementation of the OneFIT scenarios for opportunistic coverage extension, opportunistic capacity extension, infrastructure supported ad-hoc networking and device-to-device communication as well as opportunistic resource aggregation in the backhaul network

Pasquale del Pezzo, Duke of Caianello, Neapolitan mathematician

This article is dedicated to a reconstruction of some events and achievements, both personal and scientific, in the life of the Neapolitan mathematician Pasquale del Pezzo, Duke of Caianello

Results analysis and validation - D5.3

This deliverable describes the validation processes followed to assess the performance of the algorithms and protocols for the operator governed opportunistic networking as defined in the OneFIT Project. Therefore, this document includes the description of the set-up of the different validation platforms, the design of the test plans for each one of them, and the analysis of the results obtained from the tests. A per-scenario approach rather than a per-platform approach has been followed, so an additional analysis has been performed, gathering the results related to each scenario, in order to validate the premises stated to each one of them. The OneFIT concept has been therefore validated for all foreseen business scenarios