Adaptive Multicell 3D Beamforming in Multi-Antenna Cellular Networks

We consider a cellular network with multi-antenna base stations (BSs) and single-antenna users, multicell cooperation, imperfect channel state information, and directional antennas each with a vertically adjustable beam. We investigate the impact of the elevation angle of the BS antenna pattern, denoted as tilt, on the performance of the considered network when employing either a conventional single-cell transmission or a fully cooperative multicell transmission. Using the results of this investigation, we propose a novel hybrid multicell cooperation technique in which the intercell interference is controlled via either cooperative beamforming in the horizontal plane or coordinated beamfroming in the vertical plane of the wireless channel, denoted as adaptive multicell 3D beamforming. The main idea is to divide the coverage area into two disjoint vertical regions and adapt the multicell cooperation strategy at the BSs when serving each region. A fair scheduler is used to share the time-slots between the vertical regions. It is shown that the proposed technique can achieve performance comparable to that of a fully cooperative transmission but with a significantly lower complexity and signaling requirements. To make the performance analysis computationally efficient, analytical expressions for the user ergodic rates under different beamforming strategies are also derived.Comment: Accepted for publication in IEEE Transaction on Vehicular Technolog

Sum Rate Analysis of MU-MIMO with a 3D MIMO Base Station Exploiting Elevation Features

Although the three-dimensional (3D) channel model considering the elevation factor has been used to analyze the performance of multiuser multiple-input multiple-output (MU-MIMO) systems, less attention is paid to the effect of the elevation variation. In this paper, we elaborate the sum rate of MU-MIMO systems with a 3D base station (BS) exploiting different elevations. To illustrate clearly, we consider a high-rise building scenario. Due to the floor height, each floor corresponds to an elevation. Therefore, we can analyze the sum rate performance for each floor and discuss its effect on the performance of the whole building. This work can be seen as the first attempt to analyze the sum rate performance for high-rise buildings in modern city and used as a reference for infrastructure

D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Application of NOMA for cellular-connected UAVs: opportunities and challenges

Unmanned aerial vehicles (UAVs) have gained considerable interests in numerous civil applications. To push forward its potentials, cellular-connected UAVs have been introduced. Nevertheless, cellular networks face several bottlenecks such as spectrum scarcity and limited concurrent connectivity. To address these issues, non-orthogonal multiple access (NOMA) can be adopted. NOMA provides several opportunities for cellular-connected UAVs such as larger rate region, balanced performance between system throughput and fairness, and reduced delay. In this paper, we review important findings of the related studies, and outline new opportunities and challenges in NOMA for cellular-connected UAVs. Monte-Carlo simulations are then performed to analyze the new aerial user’s (AU)’s signal characteristics and evaluate the NOMA performance for co-existence of AU and terrestrial user (TU). Our preliminary results show that NOMA is a promising strategy for cellular-connected UAVs

Quasi-deterministic channel modeling and experimental validation in cooperative and massive MIMO deployment topologies

Das enorme Wachstum des mobilen Datenaufkommens wird zu substantiellen Veränderungen in mobilen Netzwerken führen. Neue drahtlose Funksysteme müssen alle verfügbaren Freiheitsgrade des Übertragungskanals ausnutzen um die Kapazität zu maximieren. Dies beinhaltet die Nutzung größerer Bandbreiten, getrennter Übertragungskanäle, Antennenarrays, Polarisation und Kooperation zwischen Basisstationen. Dafür benötigt die Funkindustrie Kanalmodelle, welche das wirkliche Verhalten des Übertragungskanals in all diesen Fällen abbilden. Viele aktuelle Kanalmodelle unterstützen jedoch nur einen Teil der benötigten Funktionalität und wurden nicht ausreichend durch Messungen in relevanten Ausbreitungsszenarien validiert. Es ist somit unklar, ob die Kapazitätsvorhersagen, welche mit diesen Modellen gemacht werden, realistisch sind. In der vorliegenden Arbeit wird ein neuen Kanalmodell eingeführt, welches korrekte Ergebnisse für zwei wichtige Anwendungsfälle erzeugt: Massive MIMO und Joint-Transmission (JT) Coordinated Multi-Point (CoMP). Dafür wurde das häufig verwendete WINNER Kanalmodell um neue Funktionen erweitert. Dazu zählen 3-D Ausbreitungseffekte, sphärische Wellenausbreitung, räumliche Konsistenz, die zeitliche Entwicklung von Kanälen sowie ein neues Modell für die Polarisation. Das neue Kanalmodell wurde unter dem Akronym "QuaDRiGa" (Quasi Deterministic Radio Channel Generator, dt.: quasideterministischer Funkkanalgenerator) eingeführt. Um das Modell zu validieren wurden Messungen in Dresden und Berlin durchgeführt. Die Messdaten wurden zunächst verwendet um die Modellparameter abzuleiten. Danach wurden die Messkampagnen im Modell nachgestellt um die Reproduzierbarkeit der Ergebnisse nachzuweisen. Essentielle Leistungsindikatoren wie z.B. der Pfadverlust, die Laufzeitstreuung, die Winkelstreuung, der Geometriefaktor, die MIMO Kapazität und die Dirty-Paper-Coding Kapazität wurden für beide Datensätze berechnet. Diese wurden dann miteinander sowie mit Ergebnissen aus dem Rayleigh i.i.d. Modell und dem 3GPP-3D Kanalmodell verglichen. Für die Messungen in Dresden erzeugt das neue Modell nahezu identische Ergebnisse wenn die nachsimulierten Kanäle anstatt der Messdaten für die Bestimmung der Modellparameter verwendet werden. Solch ein direkter Vergleich war bisher nicht möglich, da die vorherigen Modelle keine ausreichend langen Kanalsequenzen erzeugen können. Die Kapazitätsvorhersagen des neuen Modells sind zu über 90% korrekt. Im Vergleich dazu konnte das 3GPP-3D Model nur etwa 80% Genauigkeit aufweisen. Diese Vorhersagen konnten auch für das Messszenario in Berlin gemacht werden, wo mehrere Basisstationen zeitgleich vermessen wurden. Dadurch konnten die gegenseitigen Störungen mit in die Bewertung eingeschlossen werden. Die Ergebnisse bestätigen die generelle Annahme, dass es möglich ist den Ausbreitungskanal sequenziell für einzelne Basisstationen zu vermessen und danach Kapazitätsvorhersagen für ganze Netzwerke mit der Hilfe von Modellen zu machen. Das neue Modell erzeugt Kanalkoeffizienten welche ähnliche Eigenschaften wie Messdaten haben. Somit können neue Algorithmen in Funksystemen schneller bewertet werden, da es nun möglich ist realistische Ergebnisse in einem frühen Entwicklungsstadium zu erhalten.The tremendous growth of mobile data traffic will lead to substantial architectural changes in wireless networks. New wireless systems need to exploit all available degrees of freedom in the wireless channel such as wider bandwidth, multi-carrier operation, large antenna arrays, polarization, and cooperation between base stations, in order to maximize the performance. The wireless industry needs channel models that reproduce the true behavior of the radio channel in all these use cases. However, many state-of-the-art models only support parts of the required functionality and have not been thoroughly validated against measurements in relevant propagations scenarios. It is therefore unclear if the performance predictions made by these models are realistic. This thesis introduces a new geometry-based stochastic channel model that creates accurate results for two important use cases: massive multiple-input multiple-output (MIMO) and joint transmission (JT) coordinated multi-point (CoMP). For this, the popular WINNER channel model was extended to incorporate 3-D propagation, spherical wave propagation, spatial consistency, temporal evolution of channels, and a new model for the polarization. This model was introduced under the acronym ``QuaDRiGa'' - quasi deterministic radio channel generator. To validate the model, measurements were done in downtown Dresden, Germany, and downtown Berlin, Germany. Those were used to derive the model parameters. Then, the measurements were resimulated with the new channel model and benchmarked against the Rayleigh i.i.d. model and the 3GPP-3D channel model. Essential performance indicators such as path gain, shadow fading, delay spread, angular spreads, geometry factor, single-link capacity, and the dirty-paper coding capacity were computed from both the measured and resimulated data. In Dresden, the resimulated channels produce almost identical results as the measured channels. When using the resimulated channels to derive the model parameters, the same results can be obtained as when using the measurement data. Such a direct comparison was not possible with the previous models because they cannot produce sufficiently long sequences of channel data. The performance predictions from the new model are more than 90% accurate whereas only 80% accuracy could be achieved with the 3GPP-3D model. In Berlin, accurate performance predictions could also be made in a multi-cellular environment where the mutual interference between the base stations could be studied. This confirms that it is generally sufficient to use single-link measurements to parameterize channel models that are then used to predict the achievable performance in wireless networks. The new model can generate channel traces with similar characteristics as measured data. This might speed up the evaluation of new algorithms because it is now possible to obtain realistic performance results already in an early stage of development