光分插复用器:提高下一代通信网络的高传输比特率

Dunya Zeki Mohammed
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引用次数: 0

摘要

通过考虑使用基于波分复用(DWDM)新技术的光分插复用器(OADM),电信领域的光网络发展正变得越来越近。当前研究的目的是利用基于 DWDM 的光分插复用器技术,研究下一代光通信网络的高传输比特率。研究人员通过 MATLAB 软件开发了人工神经网络(ANN),用于预测在不同光缆长度(如 L=200、250 和 300 千米)下的三个主要参数,如传输信号功率(PT)、传输信号带宽(B.Wsig)和传输比特率容量(Bsh)。方差分析结果表明,在 200、250 和 300 千米条件下,预测 PT 与传输信道数 (Nch) 的函数关系的标准误差 (SE) 分别为 0.115 mW、0.095 mW 和 0.077 mW。此外,对于 200、250 和 300 公里,预测 B.Wsig 的 SE 分别为 0.067 GHz、0.051 GHz 和 0.040 GHz。最后,对于 200、250 和 300 公里,预测 Bsh 的 SE 分别为 1.665、1.311 Gbit/sec 和 1.076Gbit/sec。预测 PT 与信号波长 (λ) 关系的 SE 值在 200、250 和 300 公里分别为 0.116、0.096 和 0.079 毫瓦。此外,对于 200、250 和 300 千米,预测 B.Wsig 的 SE 分别为 0.067、0.052 和 0.052 千兆赫。最后,预测 Bsh 的 SE 值在 200、250 和 300 公里分别为 1.688、1.417 和 1.110 Gbit/sec。ANNs 的 SE 很低,这表明其效率很高,激励人们进一步优化高比特率传输的网络性能。
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Optical Add-Drop Multiplexers: Enhancing High Transmission Bit Rates in Next-Generation Communication Networks
The development of optical networks in the telecommunications sector is becoming much closer by considering the help of an Optical Add Drop Multiplexer (OADM) based on a novel technology called Wavelength Division Multiplexing (DWDM). The objective of the current study to examine high transmission bit rates for next-generation optical communication networks using the technology of OADM Based on DWDM. Artificial neural networks (ANNs) were developed via MATLAB software to predict three main parameters in this filed such as transmitted signal power (PT), transmitted signal bandwidth (B.Wsig), and transmission bit rate capacity (Bsh) at different fiber cable lengths, such as L=200, 250, and 300 km. The ANNs results showed that, standard error (SE) for predicting PT as a function of the number of transmitted channels (Nch) was 0.115 mW, 0.095 mW and 0.077 mW, for 200, 250 and 300 km, respectively. Additionally, the SE for predicting B.Wsig was 0.067 GHz, 0.051 GHz and 0.040 GHz for 200, 250 and 300 km, respectively. Lastly, the SE for predicting Bsh was 1.665, 1.311 Gbit/sec and 1.076Gbit/sec for 200, 250 and 300 km, respectively. The SE for predicting PT as a function of the Signal Wavelength (λ) was 0.116, 0.096 and 0.079 mW for 200, 250 and 300 km, respectively. Additionally, the SE for predicting B.Wsig was 0.067, 0.052 and 0.052 GHz for 200, 250 and 300 km, respectively. Lastly, the SE for predicting Bsh was 1.688, 1.417 and 1.110 Gbit/sec for 200, 250 and 300 km, respectively. The low SE in ANNs demonstrated the efficiency, motivating further advancements in optimizing network performance for high-bit-rate transmission.
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