基于DWT-ANN的DPIM信号检测器/均衡器在实际室内光无线链路中的性能

S. Rajbhandari, Zabih Ghassemlooy, M. Angelova
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摘要

人工神经网络(ANN)由于其非线性处理能力、自适应能力和并行处理能力,在通信工程中得到了广泛的应用,如信道均衡、信道建模、错误控制码等。另一方面,同时具有时间和频率分辨率的小波变换(WT)在两个域中都提供了信号的精确表示。与传统工具相比,将这些现代工具应用于通道均衡和数字信号检测中的信号处理提供了增强的性能。本文报道了采用离散小波变换(DWT)和人工神经网络(ANN)均衡的漫射室内光无线链路数字脉冲间隔调制(DPIM)的时隙误码率(SER)性能。仿真结果表明,与基于有限脉冲响应(FIR)数字滤波器的传统方法相比,该方法的性能增益约为8 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance of DWT-ANN based signal detector/equalizer for DPIM in practical indoor optical wireless links
Artificial neural network (ANN) finds its application in communication engineering in a diverse areas such as channel equalization, channel modelling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, the wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these modern tools to signal processing in channel equalization and digital signal detection provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER) performance of digital pulse interval modulation (DPIM) in diffuse indoor optical wireless links employing equalization using discrete WT (DWT) and ANN is reported. The simulation results show that a performance gain of ~8 dB is achieved by utilizing the new approach compared to the traditional approach based on the finite impulse response (FIR) digital filters.
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