利用恰好足够的SNR裕度的吞吐量最大化和信道间隔优化
Throughput Maximization Leveraging Just-Enough SNR Margin and Channel Spacing Optimization
摘要：
灵活光网络是适应下一代网络大容量需求的一种很有前途的技术。为了确保不间断的通信，现有的光路供应方案主要是在最坏情况下的资源供应不足和固定信道间隔的假设下完成的，这保留了过大的信噪比（SNR）裕度。然而，在资源过度供应场景下，过大的SNR裕度限制了传输比特率或传输范围，导致物理层资源浪费和搁浅的传输容量。为了解决这个具有挑战性的问题，我们利用迭代反馈调整算法，以提供一个刚刚足够的SNR余量，以最大限度地提高网络吞吐量。具体而言，该算法分三步实现。首先，从高信噪比裕度的设置，我们建立了一个整数线性规划模型，以及一个启发式算法，以最大化网络吞吐量通过解决路由，调制格式，前向纠错，波特率选择和频谱分配的问题。其次，我们优化了从上一步获得的光路的信道间隔，从而增加了可用的物理层资源。最后，我们迭代地降低每个光路的SNR裕度，直到网络吞吐量不能增加。通过数值模拟，我们证实了吞吐量的改善，在不同的网络和不同的波特率。特别是，我们发现，我们的算法使超过20%的相对增益时，网络资源被过度供应，相比传统的方法保留了过多的SNR余量。
英文摘要：
Flexible optical network is a promising technology to accommodate high-capacity demands in next-generation networks. To ensure uninterrupted communication, existing lightpath provisioning schemes are mainly done with the assumption of worst-case resource under-provisioning and fixed channel spacing, which preserves an excessive signal-to-noise ratio (SNR) margin. However, under a resource over-provisioning scenario, the excessive SNR margin restricts the transmission bit-rate or transmission reach, leading to physical layer resource waste and stranded transmission capacity. To tackle this challenging problem, we leverage an iterative feedback tuning algorithm to provide a just-enough SNR margin, so as to maximize the network throughput. Specifically, the proposed algorithm is implemented in three steps. First, starting from the high SNR margin setup, we establish an integer linear programming model as well as a heuristic algorithm to maximize the network throughput by solving the problem of routing, modulation format, forward error correction, baud-rate selection, and spectrum assignment. Second, we optimize the channel spacing of the lightpaths obtained from the previous step, thereby increasing the available physical layer resources. Finally, we iteratively reduce the SNR margin of each lightpath until the network throughput cannot be increased. Through numerical simulations, we confirm the throughput improvement in different networks and with different baud-rates. In particular, we find that our algorithm enables over 20\% relative gain when network resource is over-provisioned, compared to the traditional method preserving an excessive SNR margin.
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