GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Optica Publishing Group  (4)
  • Niu, Wenqing  (4)
  • Zhang, Junwen  (4)
Material
Publisher
  • Optica Publishing Group  (4)
Person/Organisation
Language
Years
  • 1
    In: Photonics Research, Optica Publishing Group, Vol. 10, No. 10 ( 2022-10-01), p. 2394-
    Abstract: Visible light communication (VLC) has emerged as a promising communication method in 6G. However, the development of receiving devices is much slower than that of transmitting devices, limited by materials, structures, and fabrication. In this paper, we propose and fabricate an InGaN/GaN multiple-quantum-well-based vertical-structure micro-LED-based photodetector (μPD) on a Si substrate. A comprehensive comparison of the photoelectrical performance and communication performance of three sizes of μPDs, 10, 50, and 100 μm, is presented. The peak responsivity of all three μPDs is achieved at 400 nm, while the passband full-widths at half maxima are 87, 72, and 78 nm for 10, 50, and 100 μm μPDs, respectively. The − 20    dB cutoff bandwidth is up to 822 MHz for 50 μm μPD. A data rate of 10.14 Gbps is experimentally demonstrated by bit and power loading discrete multitone modulation and the proposed digital pre-equalizer algorithm over 1 m free space utilizing the self-designed 4 × 4 50 μm μPD array as a receiver and a 450 nm laser diode as a transmitter. This is the first time a more than 10 Gbps VLC system has been achieved utilizing a GaN-based micro-PD, to the best of our knowledge. The investigation fully demonstrates the superiority of Si substrates and vertical structures in InGaN/GaN μPDs and shows its great potential for high-speed VLC links beyond 10 Gbps.
    Type of Medium: Online Resource
    ISSN: 2327-9125
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2022
    detail.hit.zdb_id: 2724783-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    In: Optics Express, Optica Publishing Group, Vol. 30, No. 18 ( 2022-08-29), p. 33337-
    Abstract: Recently, visible light communication (VLC) has emerged as a promising communication method in 6G. To achieve 6G high-speed transmission, wavelength division multiplexing (WDM) based VLC systems are a highly promising candidate. However, the “yellow and green gap” greatly limits the yellow light efficiency of InGaN-based LEDs and also restricts the transmission rate of yellow LEDs. In addition, pre-equalization and post-equalization also have an important impact on high-speed communication. In this paper, we propose to employ a vertical InGaN-based Si-substrate yellow LED with bit-power loading discrete multitone (DMT) modulation and a novel cascaded pre-equalizer network to achieve a high-speed yellow-light VLC system. The proposed cascaded pre-equalizer network is based on a digital Zobel network and a partial nonlinear pre-equalizer (DZNPN). The microscopic time-domain transient response of the high-speed and large-amplitude signal is also investigated to show a severe impairment. Utilizing the DZNPN cascaded pre-equalizer network based on the third-order Volterra series, a record-breaking data rate of 3.764Gbps over 1.2 m free space and 3.808Gbps over 0.7 m are experimentally demonstrated under the hard decision-forward error correction (HD-FEC) threshold of 3.8 × 10 −3 . The rate can be improved from 2.818Gbps to 3.764Gbps with 650Mbaud compared to the un-preprocessed signal. This is the highest data rate ever reported for yellow-light VLC systems based on a single LED to the best of our knowledge.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2022
    detail.hit.zdb_id: 1491859-6
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    Optica Publishing Group ; 2021
    In:  Optics Express Vol. 29, No. 14 ( 2021-07-05), p. 21773-
    In: Optics Express, Optica Publishing Group, Vol. 29, No. 14 ( 2021-07-05), p. 21773-
    Abstract: Visible light communication (VLC) system has emerged as a promising solution for high-speed underwater data transmission. To tackle with the linear and nonlinear impairments, deep learning inspired equalization is introduced into VLC. Despite their success in accuracy, deep learning approaches often come with high computational budget. In this paper, we propose an adaptive deep-learning equalizer based on complex-valued neural network and constellation partitioning scheme for 64 QAM-CAP modulated underwater VLC (UVLC) system. Inspired by the fact that symbols modulated at different levels experience various extent of nonlinear distortion, we adaptively partition the received symbols in constellation and design compact equalization networks for specific regions to reduce computation consumption. Experiments demonstrate that the partitioned equalizer can achieve the bit error rate below the 7% hard-decision forward error correction (HD-FEC) limit of 3.8 × 10 −3 at 2.85 Gbps similar to the standard complex-valued network, yet with 56.1% total computational complexity reduction. This work paves the path for online data processing in high speed UVLC system.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2021
    detail.hit.zdb_id: 1491859-6
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    Online Resource
    Online Resource
    Optica Publishing Group ; 2022
    In:  Optics Express Vol. 30, No. 22 ( 2022-10-24), p. 39466-
    In: Optics Express, Optica Publishing Group, Vol. 30, No. 22 ( 2022-10-24), p. 39466-
    Abstract: Deep neural networks (DNNs) have been applied to recover signals in optical communication systems and have shown competence of mitigating linear and nonlinear distortions. However, as the data throughput increases, the heavy computational cost of DNNs impedes them from rapid and power-efficient processing. In this paper, we propose an optical communication signal recovery technology based on a photonic convolutional processor, which is realized by dispersion delay unit and wavelength division multiplexing. Based on the photonic convolutional processor, we implement an optoelectronic convolutional neural network (OECNN) for signal post-equalization and experimentally demonstrate on 16QAM and 32QAM of an optical wireless communication system. With system parameters optimization, we verify that the OECNN can achieve accurate signal recovery where the bit error ratio (BER) is below the 7% forward error correction threshold of 3.8×10 −3 at 2Gbps. With adding the OECNN-based nonlinear compensation, compared with only linear compensation, we improve the quality (Q) factor by 3.35 dB at 16QAM and 3.30 dB at 32QAM, which is comparable to that of an electronic neural network. This work proves that the photonic implementation of DNN is promising to provide a fast and power-efficient solution for optical communication signal processing.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2022
    detail.hit.zdb_id: 1491859-6
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...