An application of reinforcement learning for efficient spectrum usage in next-generation mobile cellular networks

Authors:
Francisco Bernardo;Ramon Agustí;Jordi Pérez-Romero;Oriol Sallent
Affiliations:
Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain;Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain;Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain;Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Year:
2010

Citing 9
Cited 2

Local and global optimization algorithms for generalized learning automata

Neural Computation
Wireless Communications: Principles and Practice

Wireless Communications: Principles and Practice
Introduction to Reinforcement Learning

Introduction to Reinforcement Learning
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
Dynamic spectrum assignment in multicell OFDMA networks enabling a secondary spectrum usage

Wireless Communications & Mobile Computing - Cognitive Radio and Advanced Spectrum Management
A novel framework for dynamic spectrum management in multicell OFDMA networks based on reinforcement learning

WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
A self-organized spectrum assignment strategy in next generation OFDMA networks providing secondary spectrum access

ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Optimizing QoS routing in hierarchical ATM networks using computational intelligence techniques

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Adaptive provisioning of differentiated services networks based on reinforcement learning

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

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

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes reinforcement learning as a foundational stone of a framework for efficient spectrum usage in the context of nextgeneration mobile cellular networks. The objective of the framework is to efficiently use the spectrum in a cellular orthogonal frequency-division multiple access network while unnecessary spectrum is released for secondary spectrum usage within a private commons spectrum accessmodel. Numerical results show that the proposed framework obtains the best performance compared with other approaches for spectrum assignment. Moreover, the framework is relatively simple to implement in terms of computational requirements and signaling overhead.