Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  perform 3-Dimensional (3D) clustering based on the Outdoor-to-Indoor (O2I) wideband 3D multiple-input-multiple-output (MIMO) channel measurement at 3.5 GHz. Clusters are identified by KPorMeans algorithm. Based on analysis on clustering results,  modified the definition of Multiple component distance (MCD) to split the bounding of azimuth and elevation, which can obtain larger number of clusters and the clusters are more intra- compact and inter-separated. Then, Calinski-Harabasz (CH) and Davies-Bouldin (DB) indices are used to further validate the proposed MCD. Finally, intra cluster and inter cluster statistics are both provided, which provides insights in 3D MIMO channel modeling.
['Pan Tang', 'Jianhua Zhang', 'Yanliang Sun', 'Ming Zeng', 'Zhenzi Liu', 'Yawei Yu']
I am writing a research paper on a idea Clustering in 3D MIMO Channel: Measurement-Based Results and Improvements
[{"from": "human", "value": "I am writing a research paper on a idea Clustering in 3D MIMO Channel: Measurement-Based Results and Improvements"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  perform 3-Dimensional (3D) clustering based on the Outdoor-to-Indoor (O2I) wideband 3D multiple-input-multiple-output (MIMO) channel measurement at 3.5 GHz. Clusters are identified by KPorMeans algorithm. Based on analysis on clustering results,  modified the definition of Multiple component distance (MCD) to split the bounding of azimuth and elevation, which can obtain larger number of clusters and the clusters are more intra- compact and inter-separated. Then, Calinski-Harabasz (CH) and Davies-Bouldin (DB) indices are used to further validate the proposed MCD. Finally, intra cluster and inter cluster statistics are both provided, which provides insights in 3D MIMO channel modeling."}]