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Spectrally efficient digitized radio-over-fiber system with k-means clustering-based multidimensional quantization
Shanghai Jiao Tong University, China ; KTH Royal Institute of Technology, Sweden.
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)In: Optics Letters, ISSN 0146-9592, E-ISSN 1539-4794, Vol. 43, no 7, p. 1546-1549Article in journal (Refereed) Published
Abstract [en]

We propose a spectrally efficient digitized radio-over-fiber (D-RoF) system by grouping highly correlated neighboring samples of the analog signals into multidimensional vectors, where the k-means clustering algorithm is adopted for adaptive quantization. A 30 Gbit/s D-RoF system is experimentally demonstrated to validate the proposed scheme, reporting a carrier aggregation of up to 40 100 MHz orthogonal frequency division multiplexing (OFDM) channels with quadrate amplitude modulation (QAM) order of 4 and an aggregation of 10 100 MHz OFDM channels with a QAM order of 16384. The equivalent common public radio interface rates from 37 to 150 Gbit/s are supported. Besides, the error vector magnitude (EVM) of 8% is achieved with the number of quantization bits of 4, and the EVM can be further reduced to 1% by increasing the number of quantization bits to 7. Compared with conventional pulse coding modulation-based D-RoF systems, the proposed D-RoF system improves the signal-to-noise-ratio up to similar to 9 dB and greatly reduces the EVM, given the same number of quantization bits. (c) 2018 Optical Society of America

Place, publisher, year, edition, pages
2018. Vol. 43, no 7, p. 1546-1549
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-33817DOI: 10.1364/OL.43.001546OAI: oai:DiVA.org:ri-33817DiVA, id: diva2:1203923
Available from: 2018-05-04 Created: 2018-05-04 Last updated: 2018-05-07Bibliographically approved

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Ozolins, OskarsUdalcovs, Aleksejs

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