Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In millimeter wave networks, a received signal level and interference dynamically vary due to rain attenuation. These physical layer variations have influence on upper communication layers, which yield to variable network capabilities to serve traffic demands. Standards and agreements beten service providers and users usually specify performance objectives at annual level. In order to make realistic annual level performance analysis of such networks, a new computationally efficient dynamic rain attenuation model is proposed and analyzed. The model reproduces assumed rain statistics at annual level: cumulative distribution function (cdf) of rain intensity, number of rain events in which specified rain intensity threshold is exceeded, rain advection vector intensity, and rain advection vector azimuth. Derivation of model parameter tolerances is based on the experimental results from dense rain gauge network. As an example of model application, annual level cdfs of node-to-node connection capacity in a test network are calculated.
['Miroslav Peric', 'Dragana Peric', 'Branislav M. Todorovic', 'Miroslav Popovic']
I am writing a research paper on a idea Dynamic Rain Attenuation Model for Millimeter Wave Network Analysis
[{"from": "human", "value": "I am writing a research paper on a idea Dynamic Rain Attenuation Model for Millimeter Wave Network Analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In millimeter wave networks, a received signal level and interference dynamically vary due to rain attenuation. These physical layer variations have influence on upper communication layers, which yield to variable network capabilities to serve traffic demands. Standards and agreements beten service providers and users usually specify performance objectives at annual level. In order to make realistic annual level performance analysis of such networks, a new computationally efficient dynamic rain attenuation model is proposed and analyzed. The model reproduces assumed rain statistics at annual level: cumulative distribution function (cdf) of rain intensity, number of rain events in which specified rain intensity threshold is exceeded, rain advection vector intensity, and rain advection vector azimuth. Derivation of model parameter tolerances is based on the experimental results from dense rain gauge network. As an example of model application, annual level cdfs of node-to-node connection capacity in a test network are calculated."}]