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This article presents a novel application of the time-gating technique to the field of propagation channel study. The time-gating technique is well known in the field of antenna measurement and it is used to eliminate reflected components in outdoor measurements or anechoic chambers. In this article, we present a new measurement configuration for shielded chambers that allows to configure different propagation scenarios. In this configuration, the chamber is covered in one part with absorbers and in the other without absorbers (in order to generate reflected components). Applying the time-gating technique, we can modify, adjust and tune the reflections that a certain propagation environment has. This yields a relative control of the propagation environment in both far field and near field regions and allows to quantify the spectral efficiency and signal correlation that MIMO systems would display operating in those propagation environments.INDEX TERMS Anechoic chamber, impulse response, MIMO, recreate scenarios, reverberation chamber, time-gating.

This article presents a novel application of the t-distributed Stochastic Neighbor Embedding (t-SNE) clustering algorithm to the telecommunication field. t-SNE is a dimensionality reduction algorithm that allows the visualization of large dataset into a 2D plot. We present the applicability of this algorithm in a communication channel dataset formed by several scenarios (anechoic, reverberation, indoor and outdoor), and by using six channel features. Applying this artificial intelligence (AI) technique, we are able to separate different environments into several clusters allowing a clear visualization of the scenarios. Throughout the article, it is proved that t-SNE has the ability to cluster into several subclasses, obtaining internal classifications within the scenarios themselves. t-SNE comparison with different dimensionality reduction techniques (PCA, Isomap) is also provided throughout the paper. Furthermore, post-processing techniques are used to modify communication scenarios, recreating a real communication scenario from measurements acquired in an anechoic chamber. The dimensionality reduction and classification by using t-SNE and Variational AutoEncoders show good performance distinguishing between the recreation and the real communication scenario. The combination of these two techniques opens up the possibility for new scenario recreations for future mobile communications. This work shows the potential of AI as a powerful tool for clustering, classification and generation of new 5G propagation scenarios.

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