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K-means Clustering based Multi-Dimensional Quantization Scheme for Digital Mobile Fronthaul
KTH Royal Institute of Technology, Sweden; Shanghai Jiao Tong University, China.
RISE - Research Institutes of Sweden, ICT, Acreo. KTH Royal Institute of Technology, Sweden.
RISE - Research Institutes of Sweden, ICT, Acreo.ORCID iD: 0000-0001-9839-7488
RISE - Research Institutes of Sweden, ICT, Acreo.ORCID iD: 0000-0003-3754-0265
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We propose to group highly-correlated neighboring samples into multi-dimensional vectors and adopt k-means clustering for quantization in mobile fronthaul. 30-Gbit/s transmissions have been experimentally demonstrated for up to 40 100MHz LTE channels over 20km fiber.

Place, publisher, year, edition, pages
2018. article id Th2A.51
Keywords [en]
Long Term Evolution, pattern clustering, quantisation (signal), radio-over-fibre, vectors, digital mobile fronthaul, highly-correlated neighboring samples, multidimensional vectors, k-means clustering based multidimensional quantization scheme, LTE channels, Quantization (signal), Training, OFDM, Three-dimensional displays, Quadrature amplitude modulation, Optical fibers
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-34332DOI: 10.1364/OFC.2018.Th2A.51Scopus ID: 2-s2.0-85050013368OAI: oai:DiVA.org:ri-34332DiVA, id: diva2:1237099
Conference
Optical Fiber Communication Conference 2018 San Diego, California United States 11–15 March 2018
Available from: 2018-08-07 Created: 2018-08-07 Last updated: 2019-01-09Bibliographically approved

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Ozolins, OskarsUdalcovs, Aleksejs

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