Neural-Network-Based Fuzzy Logic Control and Decision System
IEEE Transactions on Computers - Special issue on artificial neural networks
User mobility profile prediction: an adaptive fuzzy inference approach
Wireless Networks
A Fuzzy-Neural Based Approach for Joint Radio Resource Management in a Beyond 3G Framework
QSHINE '04 Proceedings of the First International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks
Call Admission Control in Wideband CDMA Cellular Networks by Using Fuzzy Logic
IEEE Transactions on Mobile Computing
IEEE Wireless Communications
Intelligent call admission control for wideband CDMA cellular systems
IEEE Transactions on Wireless Communications
Mobility management incorporating fuzzy logic for heterogeneous a IP environment
IEEE Communications Magazine
Predictive QoS-based admission control for multiclass traffic in cellular wireless networks
IEEE Journal on Selected Areas in Communications
Adaptive resource management platform for reconfigurable networks
Mobile Networks and Applications
Proceedings of the 4th ACM symposium on QoS and security for wireless and mobile networks
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Fuzzy neural control for economic-driven radio resource management in beyond 3G networks
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Multi-criteria dynamic access selection in heterogeneous wireless networks
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Cross-layer radio resource management in integrated WWAN and WLAN networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
The E3 architecture: enabling future cellular networks with cognitive and self-x capabilities
International Journal of Network Management
Evaluation of signalling loads in a cognitive network management architecture
International Journal of Network Management
International Journal of Business Data Communications and Networking
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Inter-working and convergence of heterogeneous wireless networks are paving the way to scenarios in which end users will be capable of using simultaneously services through different Radio Access Technologies (RATs), by means of reconfigurable mobile terminals and different network elements. In order to exploit the potential of these heterogeneous networks scenarios, optimal RAT selection and resource utilization mechanisms are required. As a result, the heterogeneous networks are introducing a new dimension to the Radio Resource Management (RRM) problem, so that new algorithms dealing with the dissimilarities and complementarities of the multiple RATs from a joint perspective have to be considered. In this sense, this paper proposes a Joint Radio Resource Management (JRRM) strategy in a multi-RAT, multicellular and multiservice scenario. An approach based on Fuzzy Neural methodology is presented. Firstly, the way how the proposed Fuzzy Neural framework deals with the multiservice allocation in a heterogeneous scenario is presented. A reinforcement learning algorithm based on neural networks allows guaranteeing a multidimensional QoS focusing on those QoS requirements which mainly affect the user perception of the service. In addition to this, the performances obtained by the Fuzzy Neural JRRM for both real-time and non real-time services, are compared to the ones offered by alternative JRRM strategies. Secondly, special attention is paid to real-time services and to mechanisms to improve their performances. An approach based on predicting future JRRM decisions and on accordingly reserving radio resources for handoff calls is presented. Simulation results will show improvements in terms of both new connection blocking and handoff call dropping probabilities. Finally, the full set of results provides the sufficient insight into the problem to allow stating that the present Fuzzy Neural framework can be a firm candidate for JRRM.