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13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of York

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Output 26 of 85 in the submission

Article title

Efficient Exploration in Reinforcement Learning-based Cognitive Radio Spectrum Sharing

Type

D - Journal article

DOI

10.1049/iet-com.2010.0258

Title of journal

IET Communications

Article number

Volume number

Issue number

First page of article

1309

ISSN of journal

1751-8628

Year of publication

2011

URL

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5960412

Number of additional authors

Additional information

This paper informs new developments in cognitive radio. This paper demonstrates how reinforcement learning can be applied to cognitive radio spectrum sharing. The ideas are being used by a number of international institutions, e.g. Zhejiang University, Shanghai University and NUDT, China. The paper received the WUN CogCom Best Paper Award 2013 in the Application of Distributed Artificial Intelligence category and has provided a foundation for two EU funded projects, BuNGee (ICT 248267), led by Alvarion (oleg.marinchenco@alvarion.com) and ABSOLUTE (ICT 318632) led by Thales (isabelle.bucaille@thalesgroup.com).

Interdisciplinary

Cross-referral requested

Research group

A - Communications and Signal Processing

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract