Spectrally efficient digitized radio-over-fiber system with k-means clustering-based multidimensional quantization.

Abstract

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 100MHz orthogonal frequency division multiplexing (OFDM) channels with quadrate amplitude modulation (QAM) order of 4 and an aggregation of 10 100MHz 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 ∼9 dB and greatly reduces the EVM, given the same number of quantization bits.