Mobile communications are growing and the number of users is constantly increasing at an accelerated rate, as well as the demand for the services they request. In the last few years, many efforts have focused on the design and deployment of the new fifth generation (5G) cellular networks. However, novel highly demanding applications, which are already emerging, need to go beyond 5G in order to meet the requirements in terms of network performance. But, at the same time, as the Earth does not allow us to increase the carbon footprint anymore, the energy consumption of the communication networks has to be critically taken into consideration. A multi-objective approach for addressing all these issues is therefore required. This work develops a cellular network framework that allows the evaluation of different system parameters over dynamic traffic patterns, as well as optimizing the different conflicting objectives simultaneously. The novelty relies on that the optimization process integrates key performance indicators from different layers of the network, namely the radio and the network layers, aiming at reaching solutions that account for the power consumption of the base stations, the total capacity provided to mobile users and also the signaling cost generated by handovers. Moreover, new metrics are needed to evaluate different solutions. Starting from the well-known energy efficiency merit factor (bits/Joule), three new merit factors are proposed to classify the network performance since they take into account several network parameters at the same time. These indicators show us the ideal working point that can be used to plan the point of operation of the network. These operation points are a medium-high power and capacity load and a low signaling load.

This paper presents a general technique for the joint Direction-of-Arrival (DoA) and Time-of-Arrival (ToA) estimation in multipath environments. The proposed ultra-wideband technique is based on phase-mode expansions and the use of nearly frequency-invariant elliptical arrays. New possibilities open with the present approach, as not only elliptical, but also circular and linear (highly flattened) arrays can be considered with the same implementation. Systematic selection/rejection of signals-of-interest/signals-not-of-interest in smart wireless environments is possible, unlike with previous approaches based on circular arrays. Concentric elliptical arrays of many sizes and eccentricities can be jointly considered, with the subsequent improvement that entails in DoA and ToA detection. This leads to the realization of pseudo-random array patterns; namely, quasi-arbitrary geometries created from the superposition of multiple elliptical arrays. Some simulation and experimental tests (measurements in an anechoic chamber) are carried out for several frequency bands to check the correct performance of the method. The method is proven to give accurate estimations in all tested scenarios, and to be robust against noise and position uncertainty in sensor placement.

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.

Industrial environments constitute a challenge in terms of radio propagation due to the presence of machinery and the mobility of the different agents, especially at mmWave bands. This paper presents an experimental evaluation of a FR2 5G network deployed in an operational factory scenario at 26 GHz. The experimental characterization, performed with autonomous mobile robots that self-navigate the industrial lab, leads to the analysis of the received power along the factory and the evaluation of reference path gain models. The proposed assessment deeply analyzes the physical layer of the communication network under operational conditions. Thus, two different network configurations are assessed by measuring the power received in the entire factory, providing a comparison between deployments. Additionally, beam management procedures, such as beam recovery, beam sweeping or beam switching, are analyzed since they are crucial in environments where mobile agents are involved. They aim for a zero interruption approach based on reliable communications. The results analysis shows that beam recovery procedures can perform a beam switching to an alternative serving beam with power losses of less than 1.6 dB on average. Beam sweeping analysis demonstrates the prevalence of the direct component in Line-of-Sight conditions despite the strong scattering component and large-scale fading in the environment.

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.