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D. Denkovski, V. Rakovic, A. Ichkov, V. Atanasovski and L. Gavrilovska,
“REM-facilitated Smart WiFi”
IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN '15)
Poster track, Stockholm, Sweden, September 29 - October 2 2015
The unlicensed bands recently became overcrowded due to the WiFi networks, as the main populates of these bands. This is owed to the significant growth of WiFi users in the last decade, as well as the absence of solutions for coordinated and efficient interference management between WiFi devices. The synergy between Radio Environmental Maps (REMs) and Radio Resource Management (RRM) for Smart-WiFi, can be a viable solution to improve the spectrum utilization in the unlicensed bands and hence, WiFi performances. Environment data such as empirical propagation models, transmitters' locations, up-to-date interference levels, statistical channels occupancies, can serve as input to an enhanced RRM for these scenarios. The proposed demonstration aims to showcase the benefits of using REM information in the WiFi optimization. The demonstration utilizes a REM-facilitated Smart-WiFi prototype, performing real-time REM data acquisition, processing and inference as input to an enhanced WiFi optimization.
D. Denkovski, V. Rakovic, M. Angjelicinoski, V. Atanasovski and L. Gavrilovska,
“Small-cells radio resource management based on Radio Environmental Maps”
in proc. IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) 2014, Toronto, Canada,
April 27 - May 5 2014, pp 155-156
Recent advances in cognitive radio have identified the small-cells among the most promising future wireless networking scenarios. Utilizing radio context information, small-cells should perform the most optimal radio resource management (RRM) to maximize performances and minimize inter-cell interference. Radio Environmental Maps (REM) data: empirical propagation models, active transmitters' locations, up-to-date interference levels, statistical channels occupancies, are especially beneficial in these scenarios. The proposed demonstration aims to showcase the benefits of using REM information in the small-cell optimization. The demonstration utilizes a modular/flexible REM prototype, performing a realtime REM data acquisition, processing and inference as input to an enhanced small-cell optimization.
I. Dagres, A. Polydoros, D. Denkovski, V. Rakovic, V. Atanasovski, L. Gavrilovska, K. Cichon, A. Kliks, S. Baban and O. Holland,
“An Integrated Platform for Source Detection, Identification and Localization with Applications to Cognitive Radio”
19th European Wireless Conference - EW 2013, Guildford, UK, April 2013.
The creation of an integrated statistical-inference platform is proposed within the context of the Acropolis Network of Excellence. This platform will address aspects related to source detection, identification and localization, techniques useful in wireless-network coexistence and opportunistic spectral access. Its purpose is to integrate algorithms related to these topics under a common framework. The integration of such algorithms and the adoption of a common simulation/experimentation platform for assessing all related research will therefore be the main target of this project. The present paper is a first step of this effort, where all related algorithmic solutions available within Acropolis are presented and compared with the state of the art. The architecture of an existing experimental platform already employed for assessing some of the proposed solutions is also described.
V. Atanasovski, J. van de Beek, A. Dejonghe, D. Denkovski, L. Gavrilovska, S. Grimoud, P. Mähönen, M. Pavloski, V. Rakovic, J. Riihijärvi and B. Sayrac,
”Constructing Radio Environment Maps with Heterogeneous Spectrum Sensors”
IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN '11)
Demo track, Aachen, Germany, May 3-6, 2011.
In this demonstration proposal we describe a prototype of a radio environment map (REM) for storing and reasoning about spectrum data obtained from heterogeneous sources. The architecture of the REM prototype is both modular and extendible, and can be used with very diverse spectrum sensors, ranging from high-fidelity spectrum analyzers to dedicated low-cost embedded solutions. In the proposed demonstration we will illustrate how information such as transmitter locations and estimates of spectrum occupancy over space and time can be inferred and made available through the REM, based on information obtained from a network of different spectrum sensors deployed specifically for the demonstration.
Z. Wang, J. Ansari, V. Atanasovski, D. Denkovski, T. Farnham, L. Gavrilovska, A. Gefflaut, R. Manfrin, E. Meshkova,
J. Nasreddine, K. Rerkrai, M. Sooriyabandara and A. Zanella,
” Self-organizing Home Networking based on Cognitive Radio Technologies,”
IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN '11)
Demo track, Aachen, Germany, May 3-6.2011.
The increasing complexity of the future wireless networks leads to the requirement for self-organization. This is true especially in home networking where users are typically not networking professionals and cannot be expected to perform complex optimization and management tasks. In this context, cognitive radio concept combining cross-layer optimization and learning mechanisms is a promising solution. We demonstrate a cognitive home networking prototype, which addresses practical problems users face with the present-day wireless networks at home. The prototype shows how nodes using IEEE 802.11 radios and WARP boards operate under the Cognitive Resource Manager (CRM). The nodes achieve the desired performance by handling network dynamics and controlling parameters taking independent or cooperative decisions and operating in different layers of the protocol stack. This is done using multiple control loops which are supported by the CRM architecture. We demonstrate the use of machine learning for online estimation of network activity patterns to enable more efficient Dynamic Spectrum Access (DSA) using Hidden Semi-Markov Models (HSMM). The demonstration showcases dynamic spectrum allocation and policy-based behavioral changes in a home environment, where several multimedia streams and data communication flows are competing against each other and against external, also primary, interferers.
V. Atanasovski, D. Denkovski, T. Farnham, L. Gavrilovska, A. Gefflaut, P. Mahonen, V. Pavlovska et al.,
“Cognitive Radio for Home Networking”
IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN '10)
Demo track, Singapore, April 2010.
Cognitive Radios have emerged as one the most promising methods to increase wireless system efficiency through dynamic spectrum access combined with other cross-layer optimization methods. Most of the research prototypes and demonstrations have so far focused on either general platforms or scenarios that are predominantly taken from military or emergency communications domain. In this demonstration we show the prototype environment that is build around realistic home networking scenarios. The demonstration has two purposes. First, it demonstrates how a set of different implemented and integrated components can achieve local area optimization both in frequency allocation and other domains. Second, it shows the viability and attractiveness of cognitive radio methods for future commercial home networking devices. The demonstration showcases dynamic spectrum allocation and policy based behavioral changes in a home environment, where several multimedia stream and data communication connections are competing against each other.
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