Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  is focuses on the computation of the positive moments of one-side correlated random Gram matrices. Closed-form expressions for the moments can be obtained easily, but numerical evaluation thereof is prone to numerical stability, especially in high-dimensional settings. This letter provides a numerically stable method that efficiently computes the positive moments in closed-form. The developed expressions are more accurate and can lead to higher accuracy levels when fed to moment based-approaches. As an application,  show how the obtained moments can be used to approximate the marginal distribution of the eigenvalues of random Gram matrices.
['Khalil Elkhalil', 'Abla Kammoun', 'Tareq Y. Al-Naffouri', 'Mohamed-Slim Alouini']
I am writing a research paper on a idea Numerically Stable Evaluation of Moments of Random Gram Matrices with Applications
[{"from": "human", "value": "I am writing a research paper on a idea Numerically Stable Evaluation of Moments of Random Gram Matrices with Applications"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  is focuses on the computation of the positive moments of one-side correlated random Gram matrices. Closed-form expressions for the moments can be obtained easily, but numerical evaluation thereof is prone to numerical stability, especially in high-dimensional settings. This letter provides a numerically stable method that efficiently computes the positive moments in closed-form. The developed expressions are more accurate and can lead to higher accuracy levels when fed to moment based-approaches. As an application,  show how the obtained moments can be used to approximate the marginal distribution of the eigenvalues of random Gram matrices."}]