We experimentally observe the signal-to-noise ratio (SNR) degradation of previously established services induced by loading new services in a network, and we mitigate this degradation by periodic power re-optimization via two different strategies: (1) a static strategy based on end-of-life parameters and (2) a dynamic strategy based on real-time monitoring to the current state of the network. We use a mesh network testbed of four nodes and five links with commercial equipment only. We observe up to 3.4 dB SNR degradation on the previously established services due to the loading of new services. Then we demonstrate an improvement of up to 3.2 dB in the network margin achieved by applying our proposed power re-optimization strategy.
Experimental impact of power re-optimization in a mesh network
X. Yang;M. Tornatore;
2023-01-01
Abstract
We experimentally observe the signal-to-noise ratio (SNR) degradation of previously established services induced by loading new services in a network, and we mitigate this degradation by periodic power re-optimization via two different strategies: (1) a static strategy based on end-of-life parameters and (2) a dynamic strategy based on real-time monitoring to the current state of the network. We use a mesh network testbed of four nodes and five links with commercial equipment only. We observe up to 3.4 dB SNR degradation on the previously established services due to the loading of new services. Then we demonstrate an improvement of up to 3.2 dB in the network margin achieved by applying our proposed power re-optimization strategy.| File | Dimensione | Formato | |
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Experimental_impact_of_power_re-optimization_in_a_mesh_network.pdf
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