Técnicas de transmissão e recepção para sistemas MIMO heterogéneos na banda das ondas milimétricas

Mestrado em Engenharia Eletrónica e TelecomunicaçõesCom o crescimento dos dispositivos de comunicações móveis e de serviços de banda larga, os requisitos do sistema tornam-se cada vez mais exigentes. O LTE-Advanced apresenta um melhoramento progressivo relativamente ao seu antecessor LTE, introduzindo redes heterogéneas, que têm vindo provar constituir uma solução sólida para melhorar tanto a capacidade, como a cobertura da rede. Quanto à implementação do 5G, será necessário um salto disruptivo na tecnologia, que permita novas possibilidades, tal como a de conectar pessoas e coisas. Para tornar isso possível, é necessário investigar e testar novas tecnologias. MIMO massivo e comunicações em ondas milimétricas são algumas das tecnologias que têm vindo a demonstrar resultados com potencial, tais como o aumento da capacidade e da eficiência espectral. No entanto, devido às características da propagação de ondas milimétricas, a existência de cenários com redes heterogéneas ultradensas é uma possibilidade. Ao se considerar cenários ultradensos com um número massivo de utilizadores, o sistema fica limitado devido à interferência, mesmo operando na banda das ondas milimétricas. Como tal, é de extrema importância o desenvolvimento de técnicas que mitiguem essa interferência. Nesta dissertação, propõe-se uma arquitetura de baixa complexidade para um transmissor e um recetor a operarem no sentido ascendente, numa rede heterogénea ultradensa. Nesta arquitetura são aplicadas tecnologias como MIMO massivo, ondas milimétricas e técnicas de beamforming, com o intuito de mitigar a interferência entre células. Usando a probabilidade de erro de bit como métrica de performance, os resultados mostram que a arquitetura proposta consegue remover a interferência eficientemente, alcançando resultados próximos de uma arquitetura completamente digital.With the constant increase of mobile communication devices and broadband services, the system requirements are getting more demanding. Long Term Evolution (LTE) Advanced comes as a progressive enhancement to its predecessor LTE, introducing heterogeneous networks (HetNets), which have proven to be great solutions to improve both capacity and coverage. As for 5G, it takes more of a disruptive step, enabling new possibilities, such as connecting people and things. To enable such a step, new technologies and techniques need to be researched and tested. Massive Multiple-Input Multiple-Output (MIMO) and millimeter wave (mmWave) communications are two of such technologies, as they show promising results such as increased capacity and spectral efficiency. However, due to the mmWave propagation constraints, the existence of ultra-dense HetNet scenarios may be a possibility. When considering ultra-dense scenarios with a massive number of users, the system becomes interference-limited, even using mmWave band. As such, the design of interference mitigation techniques that deal with both inter and intra-tier interference are of the utmost importance. In this dissertation, a low complexity analog-digital hybrid architecture for both the transmitter and receiver in the uplink scenario is proposed. It is designed for an ultra-dense heterogeneous system and employing massive MIMO, mmWave and beamforming techniques in order to mitigate both intra- and inter-tier interference. Considering the Bit Error Rate (BER) as the performance metric, the results show that the proposed architecture efficiently removes both inter- and intra-tier interferences, achieving a result close to its fully digital counterpart

Fast converging robust beamforming for downlink massive MIMO systems in heterogenous networks

Massive multiple-input multiple-output (MIMO) is an emerging technology, which is an enabler for future broadband wireless networks that support high speed connection of densely populated areas. Application of massive MIMO at the macrocell base stations in heterogeneous networks (HetNets) offers an increase in throughput without increasing the bandwidth, but with reduced power consumption. This research investigated the optimisation problem of signal-to-interference-plus-noise ratio (SINR) balancing for macrocell users in a typical HetNet scenario with massive MIMO at the base station. The aim was to present an efficient beamforming solution that would enhance inter-tier interference mitigation in heterogeneous networks. The system model considered the case of perfect channel state information (CSI) acquisition at the transmitter, as well as the case of imperfect CSI at the transmitter. A fast converging beamforming solution, which is applicable to both channel models, is presented. The proposed beamforming solution method applies the matrix stuffing technique and the alternative direction method of multipliers, in a two-stage fashion, to give a modestly accurate and efficient solution. In the first stage, the original optimisation problem is transformed into standard second-order conic program (SOCP) form using the Smith form reformulation and applying the matrix stuffing technique for fast transformation. The second stage uses the alternative direction method of multipliers to solve the SOCP-based optimisation problem. Simulations to evaluate the SINR performance of the proposed solution method were carried out with supporting software-based simulations using relevant MATLAB toolboxes. The simulation results of a typical single cell in a HetNet show that the proposed solution gives performance with modest accuracy, while converging in an efficient manner, compared to optimal solutions achieved by state-of-the-art modelling languages and interior-point solvers. This is particularly for cases when the number of antennas at the base station increases to large values, for both models of perfect CSI and imperfect CSI. This makes the solution method attractive for practical implementation in heterogeneous networks with large scale antenna arrays at the macrocell base station.Dissertation (MEng)--University of Pretoria, 2018.Electrical, Electronic and Computer EngineeringMEngUnrestricte