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

A Generalized Spatial Correlation Model for 3D MIMO Channels based on the Fourier Coefficients of Power Spectrums

Previous studies have confirmed the adverse impact of fading correlation on the mutual information (MI) of two-dimensional (2D) multiple-input multiple-output (MIMO) systems. More recently, the trend is to enhance the system performance by exploiting the channel's degrees of freedom in the elevation, which necessitates the derivation and characterization of three-dimensional (3D) channels in the presence of spatial correlation. In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for 3D MIMO channels. This novel SCF is developed for a uniform linear array of antennas with nonisotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. The resulting expression depends on the underlying arbitrary angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. The developed SCF determines the covariance matrices at the transmitter and the receiver that form the Kronecker channel model. In order to quantify the effects of correlation on the system performance, the information-theoretic deterministic equivalents of the MI for the Kronecker model are utilized in both mono-user and multi-user cases. Numerical results validate the proposed analytical expressions and elucidate the dependence of the system performance on azimuth and elevation angular spreads and antenna patterns. Some useful insights into the behaviour of MI as a function of downtilt angles are provided. The derived model will help evaluate the performance of correlated 3D MIMO channels in the future.Comment: Accepted in IEEE Transactions on signal processin

Resource Allocation for Next Generation Radio Access Networks

Driven by data hungry applications, the architecture of mobile networks is moving towards that of densely deployed cells where each cell may use a different access technology as well as a different frequency band. Next generation networks (NGNs) are essentially identified by their dramatically increased data rates and their sustainable deployment. Motivated by these requirements, in this thesis we focus on (i) capacity maximisation, (ii) energy efficient configuration of different classes of radio access networks (RANs). To fairly allocate the available resources, we consider proportional fair rate allocations. We first consider capacity maximisation in co-channel 4G (LTE) networks, then we proceed to capacity maximisation in mixed LTE (including licensed LTE small cells) and 802.11 (WiFi) networks. And finally we study energy efficient capacity maximisation of dense 3G/4G co-channel small cell networks. In each chapter we provide a network model and a scalable resource allocation approach which may be implemented in a centralised or distributed manner depending on the objective and network constraints

Cloud-Based Implementation of an Automatic Coverage Estimation Methodology for Self-Organising Network

UIDB/EEA/50008/2020One of the main concerns of telecommunications operators is related to network coverage. A weak coverage can lead to a performance decrease, not only in the user experience, when using the operators' services, such as multimedia streaming, but also in the overall Quality of Service. This paper presents a novel cloud-based framework of a semi-empirical propagation model that estimates the coverage in a precise way. The novelty of this model is that it is automatically calibrated by using drive test measurements, terrain morphology, buildings in the area, configurations of the network itself and key performance indicators, automatically extracted from the operator's network. Requirements and use cases are presented as motivations for this methodology. The results achieve an accuracy of about 5 dB, allowing operators to obtain accurate neighbour lists, optimise network planning and automate certain actions on the network by enabling the Self-Organising Network concept. The cloud implementation enables a fast and easy integration with other network management and monitoring tools, such as the Metric platform, optimising operators' resource usage recurring to elastic resources on-demand when needed. This implementation was integrated into the Metric platform, which is currently available to be used by several operators.publishersversionpublishe

Analytical Models and Artificial Intelligence for Open and Partially Disaggregated Optical Networks

L'abstract è presente nell'allegato / the abstract is in the attachmen

Towards a new cloud-based planning and optimization methodology for mobile communication networks

The great concern of telecommunication operators to offer high-quality services to their customers requires a constant care with the state of the networks. These networks can present some problems that imply that the experience offered to customers is unsatisfactory. In order to monitor these situations, operators collect, on a fairly regular basis, data, like drive tests, that allow them to monitor and correct minor issues. This thesis takes advantage of the data collected and uses it in network planning in order to precisely obtain the coverage estimation of a network. In order to automate failure correction mechanisms, a totally automatic propagation model is presented, which precisely describes the state of the network, allowing it to be used for network planning and optimisation. After its implementation, the model was compared to a second model, generated through Artificial Intelligence, which is completely agnostic to all telecommunications knowledge. These models, for the considered scenarios, reached average absolute errors between estimated and actual values of 6.1 dB with a standard deviation of 4 dB. The existence of several real telecommunication network measures and their evolution to Multiple Input, Multiple Output (MIMO) systems motivated not only the investigation on the coverage impact with the change from a Single Input, Single Output (SISO) to a MIMO system, but also the investigation on the reduction of complexity of the receivers used in MIMO systems. The closer the Bit Error Rate performance of the receiver is to the Matched Filter Bound, the smaller will be the reduction in the coverage area with the transition from a SISO system to a MIMO system.A grande preocupação dos operadores de telecomunicações em oferecerem serviços de alta qualidade aos seus clientes leva a um constante cuidado com o estado das redes. Estas redes podem apresentar alguns problemas que implicam que a experiência oferecida aos clientes seja desagradável. De forma a monitorizar estas situações, os operadores recolhem, com bastante regularidade, dados, como "drive tests", que lhes permitem avaliar e corrigir pequenos problemas. Esta tese aproveita os dados recolhidos e utiliza-os no planeamento da rede de forma a obter fielmente a estimativa de cobertura de uma rede. De forma a automatizar mecanismos de correção de falhas, é apresentado um modelo de propagação completamente automático, que descreve de forma precisa o estado da rede permitindo que seja aplicado em algoritmos de planeamento e otimização da rede. Após a sua implementação, este modelo foi comparado com um segundo modelo, gerado através de inteligência artificial, que é completamente agnóstico a todo o conhecimento de telecomunicações. Estes modelos, para os cenários estudados, atingiram erros absolutos médios entre os valores estimados e os valores reais de 6.1 dB com um desvio padrão de 4 dB. A existência de diversos dados reais das redes de telecomunicações e a evolução para os sistemas "Multiple Input", "Multiple Output" (MIMO) motivou não só a investigação no impacto da cobertura com a mudança de um sistema "Single Input", "Single Output" (SISO) para um sistema MIMO, mas também a investigação na redução de complexidade dos recetores utilizados em sistemas MIMO. Quanto mais próxima a "Bit Error Rate performance" do recetor estiver do "Matched Filter Bound", menor será a redução na área de cobertura com a transição de um sistema SISO para um sistema MIMO

Improving relay based cellular networks performance in highly user congested and emergency situations

PhDRelay based cellular networks (RBCNs) are the technologies that incorporate multi-hop communication into traditional cellular networks. A RBCN can potentially support higher data rates, more stable radio coverage and more dynamic services. In reality, RBCNs still suffer from performance degradation in terms of high user congestion, base station failure and overloading in emergency situations. The focus of this thesis is to explore the potential to improve IEEE802.16j supported RBCN performance in user congestion and emergency situations using adjustments to the RF layer (by antenna adjustments or extensions using multi-hop) and cooperative adjustment algorithms, e.g. based on controlling frequency allocation centrally and using distributed approaches. The first part of this thesis designs and validates network reconfiguration algorithms for RBCN, including a cooperative antenna power control algorithm and a heuristic antenna tilting algorithm. The second part of this thesis investigates centralized and distributed dynamic frequency allocation for higher RBCN frequency efficiency, network resilience, and computation simplicity. It is demonstrated that these benefits mitigate user congestion and base station failure problems significantly. Additionally, interweaving coordinated dynamic frequency allocation and antenna tilting is investigated in order to obtain the benefits of both actions. The third part of this thesis incorporates Delay Tolerate Networking (DTN) technology into RBCN to let users self-organize to connect to functional base station through multi-hops supported by other users. Through the use of DTN, RBCN coverage and performance are improved. This thesis explores the augmentation of DTN routing protocols to let more un-covered users connect to base stations and improve network load balancin