Dynamic e-ICIC strategies based on financial techniques

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Melo, Yuri Victor Lima de
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
ABS
MAC
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/55909
Resumo: Mobile communications are preparing for the incredible changes from 4th Generation (4G) to 5th Generation (5G) in the coming years. In this new generation, co-channel interference is one of the critical challenges to be tackled due to network densification by providing high data rates through several macro and small cells working together, configuring the so-called Heterogeneous Network (HetNet). The 3rd Generation Partnership Project (3GPP) provides the Almost Blank Subframe (ABS) as a scheme of the enhanced Inter-Cell Interference Coordination (e-ICIC) framework to mitigate interference among macro and small cells. The ABS mutes some of the macro cell transmissions in selected subframes to decrease interference to small cells, thus orthogonalizing macro and small cell transmissions in the time-domain. In view of the above, this thesis uses techniques based on trading know-how to propose a real-time algorithm for ABS to improve the system capacity, that is, financial strategies are used to receive system information and provide a quick result to manage ABS while HetNet is in operation. Regarding financial strategies, this thesis uses Moving Average Crossover (MAC) and Moving Average Convergence / Divergence (MACD) that generate the trading signal, buy or sell, when they identify trends upward or downward. By the way, MAC is a strategy based on the subtraction of two Right Aligned Moving Averages (RAMAs), while MACD is a strategy that considers the historical volatility. The numerical results of MAC and MACD are compared with other algorithms in the literature by way of system-level simulations that follow some 3GPP guidelines. The results obtained by real-time strategies to buy and sell have been shown to be promising in recognizing good opportunities to allocate ABS, because they showed minimum and maximum relative gains of 12% and 112%, respectively. All in all, feasibility depends on a precise merge of the financial know-how with the wireless communication system.