Convex Channel Power Optimization in Nonlinear WDM Systems Using Gaussian Noise Model

被引:70
作者
Roberts, Ian [1 ]
Kahn, Joseph M. [1 ]
Boertjes, David [2 ]
机构
[1] Stanford Univ, Dept Elect Engn, EL Ginzton Lab, Stanford, CA 94305 USA
[2] Ciena Corp, Nepean, ON K2H 8E9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Gaussian noise model; network optimization; nonlinear capacity; optical communications; FIBER TRANSMISSION-SYSTEMS; ADAPTIVE MODULATION; GN-MODEL; PROPAGATION; NETWORKS;
D O I
10.1109/JLT.2016.2569073
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Optimization of channel powers to maximize minimum margin or total capacity in WDM systems is studied. Using a Gaussian noise nonlinearity model, the signal-to-noise ratio (SNR) in each channel is expressed as a convex function of the channel powers. Using the SNR expression, convex optimization problems with objectives of maximizing the minimum channel margin or maximizing the fiber capacity minus a coding cap are formulated. Performance gains from software-based power optimization are observed in mesh networks and in point-to-point links having heterogeneous SNR requirements. By contrast, in systems with uniform amplifier noise and modulation formats, the optimized power allocation provides very little improvement over a traditional flat power allocation. In the 14-node NSFNET network, a margin gain of 1.5 dB on average is achieved through power optimization, as compared to a flat power allocation. Margin gains averaging 1.4 dB are found for subsets of this network with three to 13 nodes.
引用
收藏
页码:3212 / 3222
页数:11
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