Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  examine the statistical distribution of the interference produced by a cluster of very many co-channel interferers, e.g., a sensor network, or a city full of active wireless devices and access points.  consider an arbitrary statistical interferer layout and consider the interference as experienced at a given point outside (and not immediately near to) the interferer area.  model the paths as experiencing por law attenuation and lognormal correlated shadowing. It has been shown in literature that adding correlation to the shadowing model can give qualitatively different (and probably more realistic) results. Our results are mostly analytical, with a small amount of numerical integration required. Whereas simulations of very many correlated interferers are very computationally heavy, our method's complexity is independent of the number of interferers, and its precision in fact improves when increasing the number of terms.
['Sebastian S. Szyszkowicz', 'Halim Yanikomeroglu']
I am writing a research paper on a idea Analysis of Interference from Large Clusters as Modeled by the Sum of Many Correlated Lognormals
[{"from": "human", "value": "I am writing a research paper on a idea Analysis of Interference from Large Clusters as Modeled by the Sum of Many Correlated Lognormals"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  examine the statistical distribution of the interference produced by a cluster of very many co-channel interferers, e.g., a sensor network, or a city full of active wireless devices and access points.  consider an arbitrary statistical interferer layout and consider the interference as experienced at a given point outside (and not immediately near to) the interferer area.  model the paths as experiencing por law attenuation and lognormal correlated shadowing. It has been shown in literature that adding correlation to the shadowing model can give qualitatively different (and probably more realistic) results. Our results are mostly analytical, with a small amount of numerical integration required. Whereas simulations of very many correlated interferers are very computationally heavy, our method's complexity is independent of the number of interferers, and its precision in fact improves when increasing the number of terms."}]