Reconfigurable Radio in Europe

Dillinger, Markus; Bourse, Didier

doi:10.1002/0470846011.ch7

Cited by 12 publications

(13 citation statements)

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“…mixers, filters, amplifiers, modulators/demodulators, detectors, etc.) are instead implemented by means of software [39,40]. However, cognitive radios should not be considered as a substitute term for SDRs, since they are expected to incorporate additional components and capabilities, enforce policies, exploit SDR reconfigurability, provide incentive and coexistence mechanisms, and further implement cognition in their operation, as explained in more detail in subsection 3.2.…”

Section: From Wireless To Mobile Cognitive Radio Networkingmentioning

confidence: 99%

Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

Karyotis

Anifantis

Papavassiliou

2014

Resource Management in Mobile Computing Environments

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Abstract.Resource management has been one of the most important aspects of Mobile Cognitive Radio Networks (MCRNs) since their inception. It engulfs fundamental network operations such as spectrum management, bandwidth allocation, channel access, data routing, transmission power assignment and energy management. All such mechanisms are necessary for achieving the delay/throughput requirements desired by modern network services and users. Compared to traditional wireless mobile networks, the MCRN environment poses additional challenges and complicated requirements to the above functions and resource management in general, which eventually lead to an urgent need for reconsideration of the employed wireless protocol stack. The objective in MCRNs would be to apply more efficient protocol hierarchies and achieve better management of the common available resources for both secondary and primary users, at the minimum possible cost and by leaving the minimum possible resource footprint, as required for all modern communications systems. The cross-layer design approach has been proven extremely useful towards this direction, especially for network types such as sensor, mesh and cognitive radios. It allowed exploiting the most appropriate network mechanisms, while bypassing monolithic and outdated requirements when possible. In this chapter, we focus exactly on this aspect of protocol architectures and network management, and present state-of-the-art cross-layer based resource management approaches for MCRNs. Initially, we present three important resource management frameworks, and then we provide directions for developing generic and adaptive resource management protocol architectures for MCRNs, based on cross-layer and component-based design principles emerging from the previously presented approaches. This is the first attempt to highlight the suitability of combining cross-layer with componentbased network design, and this work will also sketch qualitatively the potential benefits of such approach. Finally, some practical considerations for the proposed architecture, along with directions for future research conclude the chapter.

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Section: From Wireless To Mobile Cognitive Radio Networkingmentioning

confidence: 99%

Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

Karyotis

Anifantis

Papavassiliou

2014

Resource Management in Mobile Computing Environments

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“…USRP is an experimental platform of a GNU radio or software-defined radio (SDR) system where components that have been typically implemented in hardware (e.g., mixers, filters, amplifiers, modulators, demodulators, detectors, etc. ) are instead implemented by means of software on a personal computer or embedded computing devices [25]. Using two USRP mother boards equipped with BasicTX/RX and LFTX/RX daughter boards, the communication systems working on low frequency bands are established in [18].…”

Section: Wireless Signal Networkmentioning

confidence: 99%

Subsurface Event Detection and Classification Using Wireless Signal Networks

Yoon

Ghazanfari

Cheng

et al. 2012

Sensors

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Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

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“…Implementation of several standards using separate dedicated devices is noneconomical, because these devices include a lot of identical components. More convenient solution for designing of multimode and multi-standard devices can be made by using of SDR (Software Defined Radio) [2] idea with DiCon (Direct Conversion) architecture [3]. The concept requires implementation of two mechanisms: baseband block reconfigurability and RF Front-End adaptivity.…”

Section: Introductionmentioning

confidence: 99%

27 dBm Microwave Amplifiers with Adaptive Matching Networks

Rosolowski¹,

Wojtasiak²,

Gryglewski³

2011

International Journal of Electronics and Telecommunications

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27 dBm Microwave Amplifiers with Adaptive Matching Networks The paper describes adaptive amplifier design with varactors and pin diodes as regulators of matching networks. As examples the two amplifiers with SHF-0189 HFET transistor and different matching sections were designed and manufactured. The output power level of 27 dBm and gain higher than 13 dB within L and S-band have been achieved. The amplifier design methodology is based on the small-signal approach and DC characteristics of transistors and regulators. Amplifier adaptivity allows us to remotely control the chosen parameters such as: frequency range, output power level, gain and etc.

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Reconfigurable Radio in Europe

Cited by 12 publications

References 0 publications

Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

Subsurface Event Detection and Classification Using Wireless Signal Networks

27 dBm Microwave Amplifiers with Adaptive Matching Networks

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