Self-optimization of coverage and capacity based on a fuzzy neural network with cooperative reinforcement learning
- Submitting institution
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Oxford Brookes University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 186971915
- Type
- D - Journal article
- DOI
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10.1186/1687-1499-2014-57
- Title of journal
- EURASIP Journal on Wireless Communications and Networking
- Article number
- 57
- First page
- -
- Volume
- 2014
- Issue
- -
- ISSN
- 1687-1499
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The work is a result of collaboration with Beijing University of Posts and Telecommunications, and led to S. Fan completing his PhD and get hired as a post-doc at the BUPT. Self-organization is the holy grail of mobile wireless networks. This work is significant because it demonstrates for the first time how by sharing their “machine learning experience” with others, Access Points learn the best antenna tilt and transmission power for different scenarios more efficiently. The work has been included in the book “Machine Learning for Future Wireless Communications”, by IEEE Fellow Dr. Fa-Lang Luo, published by Wiley, ISBN: 978-1-119-56225-2
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -