In the LTE access networks, the Radio Resource Management (RRM) is one of the most important modules which is responsible for handling the overall management of radio resources. The packet scheduler is a particular sub-module which assigns the existing radio resources to each user in order to deliver the requested services in the most efficient manner. Data packets are scheduled dynamically at every Transmission Time Interval (TTI), a time window used to take the user’s requests and to respond them accordingly. The scheduling procedure is conducted by using scheduling rules which select different users to be scheduled at each TTI based on some priority metrics. Various scheduling rules exist and they behave differently by balancing the scheduler performance in the direction imposed by one of the following objectives: increasing the system throughput, maintaining the user fairness, respecting the Guaranteed Bit Rate (GBR), Head of Line (HoL) packet delay, packet loss rate and queue stability requirements. Most of the static scheduling rules follow the sequential multi-objective optimization in the sense that when the first targeted objective is satisfied, then other objectives can be prioritized. When the targeted scheduling objective(s) can be satisfied at each TTI, the LTE scheduler is considered to be optimal or feasible. So, the scheduling performance depends on the exploited rule being focused on particular objectives. This study aims to increase the percentage of feasible TTIs for a given downlink transmission by applying a mixture of scheduling rules instead of using one discipline adopted across the entire scheduling session. Two types of optimization problems are proposed in this sense: Dynamic Scheduling Rule based Sequential Multi-Objective Optimization (DSR-SMOO) when the applied scheduling rules address the same objective and Dynamic Scheduling Rule based Concurrent Multi-Objective Optimization (DSR-CMOO) if the pool of rules addresses different scheduling objectives. The best way of solving such complex optimization problems is to adapt and to refine scheduling policies which are able to call different rules at each TTI based on the best matching scheduler conditions (states). The idea is to develop a set of non-linear functions which maps the scheduler state at each TTI in optimal distribution probabilities of selecting the best scheduling rule. Due to the multi-dimensional and continuous characteristics of the scheduler state space, the scheduling functions should be approximated. Moreover, the function approximations are learned through the interaction with the RRM environment. The Reinforcement Learning (RL) algorithms are used in this sense in order to evaluate and to refine the scheduling policies for the considered DSR-SMOO/CMOO optimization problems. The neural networks are used to train the non-linear mapping functions based on the interaction among the intelligent controller, the LTE packet scheduler and the RRM environment. In order to enhance the convergence in the feasible state and to reduce the scheduler state space dimension, meta-heuristic approaches are used for the channel statement aggregation. Simulation results show that the proposed aggregation scheme is able to outperform other heuristic methods. When the aggregation scheme of the channel statements is exploited, the proposed DSR-SMOO/CMOO problems focusing on different objectives which are solved by using various RL approaches are able to: increase the mean percentage of feasible TTIs, minimize the number of TTIs when the RL approaches punish the actions taken TTI-by-TTI, and minimize the variation of the performance indicators when different simulations are launched in parallel. This way, the obtained scheduling policies being focused on the multi-objective criteria are sustainable. Keywords: LTE, packet scheduling, scheduling rules, multi-objective optimization, reinforcement learning, channel, aggregation, scheduling policies, sustainable.

Made available in DSpace on 2014-12-17T14:55:50Z (GMT). No. of bitstreams: 1 BrunoLMTS_DISSERT.pdf: 3836374 bytes, checksum: 430e05d393bcb665a7880036b61844c2 (MD5) Previous issue date: 2011-03-31 / This work treats of an implementation OFDMA baseband processor in hardware for LTE Downlink. The LTE or Long Term Evolution consist the last stage of development of the technology called 3G (Mobile System Third Generation) which offers an increasing in data rate and more efficiency and flexibility in transmission with application of advanced antennas and multiple carriers techniques. This technology applies in your physical layer the OFDMA technical (Orthogonal Frequency Division Multiple Access) for generation of signals and mapping of physical resources in downlink and has as base theoretical to OFDM multiple carriers technique (Orthogonal Frequency Division Multiplexing). With recent completion of LTE specifications, different hardware solutions have been developed, mainly, to the level symbol processing where the implementation of OFDMA processor in base band is commonly considered, because it is also considered a basic architecture of others important applications. For implementation of processor, the reconfigurable hardware offered by devices as FPGA are considered which shares not only to meet the high requirements of flexibility and adaptability of LTE as well as offers possibility of an implementation quick and efficient. The implementation of processor in reconfigurable hardware meets the specifications of LTE physical layer as well as have the flexibility necessary for to meet others standards and application which use OFDMA processor as basic architecture for your systems. The results obtained through of simulation and verification functional system approval the functionality and flexibility of processor implemented / Esta disserta??o trata da implementa??o de um processador banda base em hardware para Downlink LTE. O LTE ou Long Term Evolution compreende o ?ltimo est?gio de desenvolvimento das tecnologias chamadas de 3G (Telefonia M?vel de Terceira Gera??o) que prov? um incremento nas taxas de dados e maior efici?ncia e flexibilidade na transmiss?o com emprego de t?cnicas avan?adas de antenas e de t?cnicas de transmiss?o de m?ltiplas portadoras. Esta tecnologia aplica em sua camada f?sica a t?cnica OFDMA (Orthogonal F requency Division Multiple Access) para gera??o de sinais e mapeamento dos recursos f?sicos no downlink e tem como base te?rica ? t?cnica de m?ltiplas portadoras OFDM (Orthogonal Frequency Division Multiplexing). Com recente finaliza??o das especifica??es da tecnologia LTE, diversas solu??es em hardware tem sido propostas e desenvolvidas, principalmente, ao n?vel de processamento de s?mbolo em que a implementa??o do processador OFDMA em banda base ? comumente considerada, visto que ela ? tamb?m considerada como arquitetura b?sica de outras importantes aplica??es. Para implementa??o do processador, hardwares reconfigur?veis oferecidos por dispositivos como FPGA s?o considerados que visa n?o s? atender os altos requisitos de flexibilidade e adaptabilidade do LTE como tamb?m oferecem a possibilidade de uma implementa??o r?pida e eficiente. A implementa??o do processador em hardware reconfigur?vel atendeu as especifica??es da camada f?sica LTE bem como se mostrou flex?vel o suficiente para atender outros padr?es e aplica??es que utilizem o processador OFDMA como arquitetura b?sica de seus sistemas. Os resultados obtidos atrav?s de simula??o e verifica??o funcional do sistema atestam a funcionalidade e a flexibilidade do processador implementado