Joint Precoding and RRH Selection for User-Centric Green MIMO C-RAN
- Submitting institution
-
Queen Mary University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 482
- Type
- D - Journal article
- DOI
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10.1109/TWC.2017.2671358
- Title of journal
- IEEE Transactions on Wireless Communications
- Article number
- -
- First page
- 2891
- Volume
- 16
- Issue
- 5
- ISSN
- 1536-1276
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- 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
-
3
- Research group(s)
-
-
- Citation count
- 91
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposed a novel user-centric network architecture for ultra-dense networks with reduced computational complexity. Both the low-complexity user selection algorithm and network power consumption minimization method were proposed. Work kick-started by Nathan?s (n.j.gomes@kent.ac.uk) EU project (https://cordis.europa.eu/project/id/644526) and EPSRC standard project (https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/L026031/1), and was key technology in securing the follow-up Horizon 2020 project 5G-DRIVE between EU and China to develop high-speed 5G networks (No 814956, 2018, https://5g-drive.eu/). Paper was Web of Science highly cited paper and the most frequently downloaded paper in May 2017 (https://ieeexplore.ieee.org/xpl/topAccessedArticles.jsp?punumber=7693&topArticlesDate=May%202017)
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -