As early as 2014, mobile network operators' spectral capacity will be overwhelmed by the demand brought on by new devices and applications. To augment capacity and meet this demand, operators may choose to deploy a Dynamic Spectrum Access (DSA) overlay. Spectrum regulation is following suit, with regulators attempting to incorporate spectrum sharing through the design of spectrum access rules that support DSA. This dissertation explores the idea of DSA applied to Long Term Evolution Advanced (LTE+) networks. This idea is explored under functional, architectural, and spectrum policy aspects. Under the functional and architectural aspects of this topic, the signaling and functionality required by such an overlay have not yet been fully considered in the architecture of an LTE+. This dissertation presents a Spectrum Accountability framework to be integrated into LTE+ MacroNet and HetNet architectures, defining specific element functionality, protocol interfaces, and signaling flow diagrams required to enforce the rights and responsibilities of primary and secondary users. We also identify and propose three DSA management frameworks for LTE+ HetNets: Spectrum Accountability Client Only, Cell Spectrum Management, and Domain Spectrum Management. Our Spectrum Accountability framework may serve as a guide in the development of future LTE+ network standards that account for DSA. We also quantify, through simulation and integer programs, the benefits of using DSA channels to augment capacity under a scenario in which LTE+ network can opportunistically use TV and GSM spectrum. In our first experiment, we a consider a scenario where three different operators share the same cell site with LTE+ equipment and a Dynamic Spectrum Access (DSA) band to augment spectral capacity. Our experiments show that throughput can increase by as much as 40%. We develop integer programs to model the assignment of spectrum channels to both a MacroNet and HetNet. In our selected scenario, we observe TV white spectrum provides the largest gain in performance for both Nets: 27% for MacroNet and 9% increase for the HetNet over our measured ranges. Although the gains in using opportunistic use of GSM is more modest, 10% and 2% for the Macro and HetNet, respectively, we believe that these gains will significantly increase as operators continue to migrate users to LTE+, thus freeing up portions of the bands currently used for GSM service. In our final analytical model, we create integer program sets to represent the different three DSA management frameworks for LTE+ HetNets and compare their results. Under the spectrum policy aspects, this dissertation develops a decision-theoretic framework for regulators to assess the impacts of different spectrum access rules on both primary and secondary operators. We analyze access rules based on sensing and exclusion areas, which in practice can be enforced through geolocation databases. Our results show that receiver-only sensing provides insufficient protection for primary and co-existing secondary users and overall low social welfare. On the other hand, combining sensing information of only the transmitter and receiver of a communication link provides dramatic increases in system performance. The performance of using these link end points is relatively close to that of using many cooperative sensing nodes associated to the same access point and large link exclusion areas. We hope these results will prove useful to regulators and network developers in un and developing rules for future DSA regulation. / Ph. D.

Submitted by Automação e Estatística (sst@bczm.ufrn.br) on 2018-04-11T20:06:38Z No. of bitstreams: 1 BrunoJacomeCavalcanti_TESE.pdf: 5397909 bytes, checksum: 5a245eec570a69adf8ca5d791aaddf70 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2018-04-16T20:46:19Z (GMT) No. of bitstreams: 1 BrunoJacomeCavalcanti_TESE.pdf: 5397909 bytes, checksum: 5a245eec570a69adf8ca5d791aaddf70 (MD5) / Made available in DSpace on 2018-04-16T20:46:19Z (GMT). No. of bitstreams: 1 BrunoJacomeCavalcanti_TESE.pdf: 5397909 bytes, checksum: 5a245eec570a69adf8ca5d791aaddf70 (MD5) Previous issue date: 2017-10-20 / A perfeita funcionalidade dos sistemas de comunicações de 3ª. e 4ª. gerações requerem, entre outras coisas, do conhecimento dos valores numéricos da predição das perdas de propagação dos sinais propagantes nos ambientes urbano, suburbano e rural. Portanto, o estudo das condições de propagação em um ambiente qualquer sempre será uma preocupação dos engenheiros projetistas. A análise e desenvolvimento de modelos robustos de predição de perdas de propagação em redes de comunicações Long Term Evolution (LTE) e Long Term Evolution Advanced (LTE-A) usando técnicas de Inteligência Artificial são realizadas neste trabalho. Os procedimentos metodológicos empregados foram aplicados no melhoramento da predição dos modelos de perda de propagação empíricos SUI, ECC-33, Ericsson 9999, TR 36.942 e o modelo do Espaço Livre, aplicados em redes LTE e LTE-A nas frequências de 800 MHz, 1800 MHz e 2600 MHz, para ambientes suburbanos em cidades de porte médio do nordeste do Brasil. Assim, nesta tese propõem-se dois modelos de Redes Neurais Artificiais (RNA): (i) o modelo de rede neural com entradas baseadas em erro (RNBE), utilizando como principal alimentador da rede o erro entre dados medidos e simulados, e, (ii) o modelo de rede neural com entradas baseadas no terreno (RNBT). O desempenho desses modelos foram comparados com os modelos de propagação considerados no trabalho e também as versões otimizadas utilizando Algoritmos Genéticos (AG) e o Método dos Mínimos Quadrados (LMS). Também foram realizadas comparações com valores medidos, obtidos a partir de uma campanha de medição realizada na cidade de Natal, Estado do Rio Grande do Norte. Os resultados finais obtidos através de simulações e medições apresentaram boas concordâncias métricas, com destaque para a performance do modelo RNBE. A principal contribuição dessa tese é que, ao utilizar essas técnicas que fazem uso de maneira mais eficiente dos modelos de propagação empíricos, pode-se estimar sinais propagantes realistas, evitando erros no planejamento e implementações de redes sem fio LTE e LTE-A em áreas suburbanas. / The perfect functionality of the 3rd and 4th generation of wireless systems requires, among other parameters, knowledge of the numerical values of the prediction of loss of propagation of propagation signals in urban, suburban and rural environments. Therefore, the study of propagation conditions in any environment will always be a concern of design engineers. The analysis and development of robust propagation loss prediction models in Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A) communications networks using Artificial Intelligence techniques is performed in this work. The methodologies used were applied to improve the prediction of loss of empirical propagation SUI, ECC-33, Ericsson 9999, TR 36.942 models and the Free Space model applied in LTE and LTE-A networks in the frequencies of 800 MHz, 1800 MHz and 2600 MHz, for suburban environments in mid-sized cities in northeastern Brazil. Thus, in these thesis two models of Artificial Neural Networks (RNA) are proposed: (i) the neural network model with inputs based on error (RNBE) using as main feeder of the network the error between measured and simulated data, and (ii) the neural network model with land-based inputs (RNBT). The performance of these models was compared with the models of propagation considered in the work and also the versions optimized using Genetic Algorithms (AG) and the Least Square Method (LMS). Comparisons were also made with measured values, obtained from a measurement campaign carried out in the city of Natal, state of Rio Grande do Norte. The final results obtained through simulations and measurements presented good metric concordances, with emphasis on the performance of the RNBE model. Thus, the main contribution of this thesis is that, by using these techniques that make more efficient use of empirical propagation models, we can estimate realistic propagation signals, avoiding errors in the planning and implementations of LTE and LTE- A wireless networks in suburban areas.