Compared with optical networks-on-chip (ONoCs) based on traditional topology such as mesh, torus, and fat-tree, Gaussian-based ONoCs have significant topological advantages in the network diameter and average jump distance. However, the intrinsic loss and crosstalk noise, which are inevitably inherent elements in basic optical devices, can lead to severe degradation of network performance and even restrict the normal communication of ONoCs. Therefore, in this paper, a numerical analysis model for analyzing the worst-case crosstalk noise and optical signal-to-noise ratio (OSNR) in Gaussian-based ONoCs is proposed. According to the all-pass characteristic of Gaussian-based ONoCs, the 5-ports all-pass optical routers are selected, which make the proposed model suitable for Gaussian-based ONoCs using arbitrary 5-ports all-pass optical routers. In addition, a numerical simulation is presented, which uses the Cygnus and optimized crossbar optical routers to verify the feasibility of the proposed analytical model. The simulation results show that the OSNR of Gaussian-based ONoCs decreases sharply with the network scale enlargement, the insertion loss and crosstalk noise tremendously limits the network scale. Furthermore, in order to make the Gaussian-based ONoCs more available, an optimization method is also proposed for improving network performance. The optimization method choose the best optical link between two arbitrary communication points, which can effectively avoid the worst case and greatly improve the performance of Gaussian-based ONoCs.

与基于传统拓扑（例如网格，圆环和胖树）的片上光学网络（ONoC）相比，基于高斯的ONoC在网络直径和平均跳跃距离方面具有明显的拓扑优势。但是，固有损耗和串扰噪声是基本光学设备中不可避免的固有要素，会导致网络性能严重下降，甚至会限制ONoC的正常通信。因此，本文提出了一种数值分析模型，用于分析基于高斯的ONoC的最坏情况串扰噪声和光信噪比（OSNR）。根据基于高斯的ONoC的全通特性，选择5端口全通光路由器，从而使该模型适用于使用任意5端口全通光路由器的高斯ONoC。此外，提出了一个数值模拟，它使用天鹅座和优化的纵横制光路由器来验证所提出的分析模型的可行性。仿真结果表明，基于高斯的ONoC的OSNR随着网络规模的扩大而急剧下降，插入损耗和串扰噪声极大地限制了网络规模。此外，为了使基于高斯的ONoC更加可用，还提出了一种用于改善网络性能的优化方法。该优化方法选择了任意两个通信点之间的最佳光链路，可以有效避免最坏情况，大大提高了基于高斯的ONoC的性能。它使用Cygnus和优化的纵横制光路由器来验证所提出的分析模型的可行性。仿真结果表明，基于高斯的ONoC的OSNR随着网络规模的扩大而急剧下降，插入损耗和串扰噪声极大地限制了网络规模。此外，为了使基于高斯的ONoC更加可用，还提出了一种用于改善网络性能的优化方法。该优化方法选择了任意两个通信点之间的最佳光链路，可以有效避免最坏情况，大大提高了基于高斯的ONoC的性能。它使用Cygnus和优化的纵横制光路由器来验证所提出的分析模型的可行性。仿真结果表明，基于高斯的ONoC的OSNR随着网络规模的扩大而急剧下降，插入损耗和串扰噪声极大地限制了网络规模。此外，为了使基于高斯的ONoC更加可用，还提出了一种用于改善网络性能的优化方法。该优化方法选择了任意两个通信点之间的最佳光链路，可以有效避免最坏情况，大大提高了基于高斯的ONoC的性能。插入损耗和串扰噪声极大地限制了网络规模。此外，为了使基于高斯的ONoC更加可用，还提出了一种用于改善网络性能的优化方法。该优化方法选择了任意两个通信点之间的最佳光链路，可以有效避免最坏情况，大大提高了基于高斯的ONoC的性能。插入损耗和串扰噪声极大地限制了网络规模。此外，为了使基于高斯的ONoC更加可用，还提出了一种用于改善网络性能的优化方法。该优化方法选择了任意两个通信点之间的最佳光链路，可以有效避免最坏情况，大大提高了基于高斯的ONoC的性能。