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Quantitative analysis of the stacked autoencoder method in MIMO-ACO-OFDM VLC systems

机译:MIMO-ACO-OFDM VLC系统中堆叠自动化器方法的定量分析

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摘要

In this paper, a stacked autoencoder network is utilised to realise the signal constellation and transceivers adapted to the dimmable indoor visible light communication system in order to acquire lower symbol error probability. Its decoder parts function as denoising and the equaliser for the proposed multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) visible light communication system which can compensate the non-linear transfer function and the crosstalk between multiple LED data streams. The bit error rate performance as well as the influence of LED spatial intervals on root mean square delay spread, impulse response and bit rate have been analysed considering multipath reflections of the indoor MIMO-VLC system. The numerical results show that the a stacked autoencoder technique performs better in bit error rate reduction compared with state-of-art the zero forcing and minimum mean squared error algorithm. The experiment also shows, when the semi-angle at half power of LEDs and the field of view of Photodetectors become small, better performance can be achieved at the centre of the room, which can be explained by strong beam converge and the decreased multipath interference. Moreover, enlarging the separation between LEDs leads to improved bit error rate performance and reduced channel correlation of channel matrix, which need to be optimally chosen in practice.
机译:在本文中,利用堆叠的AutoEncoder网络来实现适用于可调光室内可见光通信系统的信号星座和收发器,以便获取较低的符号误差概率。其解码器零件用作去噪和均拟的多输入多输出(MIMO)正交频分复用(OFDM)可见光通信系统的均衡器,其可以补偿非线性传递函数和多个LED数据流之间的串扰。考虑到室内MIMO-VLC系统的多径反射,已经分析了误码率性能以及LED空间间隔对均方延迟扩展,脉冲响应和比特率的影响。数值结果表明,与零强制和最小均方误差算法相比,堆叠的自动统计器技术以误码率降低执行更好。实验还示出,当LED的半角和光电探测器的视野变小时,可以在房间的中心实现更好的性能,这可以通过强光束汇聚和减少的多径干扰来解释。 。此外,扩大LED之间的分离导致提高的误码率性能和信道矩阵的沟道相关性,这需要在实践中最佳地选择。

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  • 来源
    《Lighting Research & Technology》 |2021年第1期|54-73|共20页
  • 作者

    LL Hao; CD Li; DY Wang;

  • 作者单位

    School of Information and Electrical Engineering Shandong Jianzhu University Jinan P.R. China Bio-lmaging and Machine Vision Lab Fischell Department of Bioengineering University of Maryland College Park MD USA;

    School of Information and Electrical Engineering Shandong Jianzhu University Jinan P.R. China;

    Bio-lmaging and Machine Vision Lab Fischell Department of Bioengineering University of Maryland College Park MD USA;

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