基于RSOA的4PAM信号4PAM-RSOA无色ONU实验与理论分析

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本文主要探讨了一种基于反射半导体光放大器(RSOAs)的无色光网络单元(ONU)设计,该设计采用了4级脉冲幅度调制(4PAM)信号作为上行链路的重映射信号。这一创新方案旨在提升上行数据传输的性能,尤其是在处理高速非归零(NRZ)下行链路(10 Gb/s)与5 Gb/s 4PAM上行信号的系统中。 研究者们首先从理论角度对这个系统进行了深入分析,考虑了4PAM信号相较于NRZ信号在光放大、噪声特性以及信号稳定性方面的优势。4PAM信号由于其更高的阶跃性,能够在有限的带宽内提供更高的数据速率,从而可能降低误码率,提高信号质量。此外,4PAM信号的非线性效应可能会通过RSOAs得到一定程度的抑制,减少了对下游信号的干扰,进一步提升了系统的整体效率。 实验部分,研究团队实施了一系列实际测试来验证理论预测。他们对4PAM重映射ONU的性能进行了细致的测量,包括接收功率损失(receiver power penalty)等关键指标。实验结果显示,与NRZ信号相比,4PAM信号在上行链路中的表现更为出色,这表明采用4PAM信号可以实现更高效的信号传输和更小的误码率。 值得注意的是,这项研究对于光网络技术的发展具有重要意义,因为它提供了一种潜在的技术路径,使得在网络边缘节点(如ONU)利用低成本的RSOAs实现高效的数据交换成为可能,特别是在上行链路容量受限的场景中。同时,这也为未来的无色网络架构(colorless OLT/ONU)设计提供了有价值的经验和参考。 总结来说,这篇文章深入探讨了4PAM信号在RSOAs支持的无色ONU中的应用,并通过理论分析和实验验证证明了它在上行链路优化中的优势。这对于提高光纤通信系统的整体性能和适应不断增长的数据传输需求具有重要的实践意义。

4 Experiments This section examines the effectiveness of the proposed IFCS-MOEA framework. First, Section 4.1 presents the experimental settings. Second, Section 4.2 examines the effect of IFCS on MOEA/D-DE. Then, Section 4.3 compares the performance of IFCS-MOEA/D-DE with five state-of-the-art MOEAs on 19 test problems. Finally, Section 4.4 compares the performance of IFCS-MOEA/D-DE with five state-of-the-art MOEAs on four real-world application problems. 4.1 Experimental Settings MOEA/D-DE [23] is integrated with the proposed framework for experiments, and the resulting algorithm is named IFCS-MOEA/D-DE. Five surrogate-based MOEAs, i.e., FCS-MOEA/D-DE [39], CPS-MOEA [41], CSEA [29], MOEA/DEGO [43] and EDN-ARM-OEA [12] are used for comparison. UF1–10, LZ1–9 test problems [44, 23] with complicated PSs are used for experiments. Among them, UF1–7, LZ1–5, and LZ7–9 have 2 objectives, UF8–10, and LZ6 have 3 objectives. UF1–10, LZ1–5, and LZ9 are with 30 decision variables, and LZ6–8 are with 10 decision variables. The population size N is set to 45 for all compared algorithms. The maximum number of FEs is set as 500 since the problems are viewed as expensive MOPs [39]. For each test problem, each algorithm is executed 21 times independently. For IFCS-MOEA/D-DE, wmax is set to 30 and η is set to 5. For the other algorithms, we use the settings suggested in their papers. The IGD [6] metric is used to evaluate the performance of each algorithm. All algorithms are examined on PlatEMO [34] platform.

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