Alocacao de blocos de recurso em redes LTE e utilizando logica fuzzy e estimacao adaptativa de banda efetiva

Carregando...
Imagem de Miniatura

Data

2015-03-19

Título da Revista

ISSN da Revista

Título de Volume

Editor

Universidade Federal de Goiás

Resumo

In this paper we propose two schemes for allocating resource blocks for transmission LTE downlink to maximize the throughput of the system, to guarantee QoS (Quality of Service) parameters for the users and reduce the data loss rate of network. The first proposed scheme uses the Max-min criterion and the second employs a fuzzy inference system to calculate the priorities of users and make scheduling decisions. Both schemes use an estimated effective bandwidth of traffic flows of users. The effective bandwidth of a traffic flow is the rate required to meet a criterion of probability of data loss rate. In this work, the effective bandwidth is estimated adaptively by the parameters of multifractal modeling βMWM (β-Multifractal Wavelet Mode). Are made simulations of the algorithms proposed, considering different propagation models with multipath fading and with different numbers of users in the network. The simulation results are compared with other algorithms presented in the literature, using parameters such as: throughput of the system, data loss rate and fairness index. It is also proposed to use predict of the SNR (Signal-to-Noise Ratio) of users, in the scheduling algorithms, using linear prediction of multi-step filter, in view of the delay in receipt of the channel quality information of the users in the base station and the variation of the signal propagation conditions. The multi-step prediction filter is used with the algorithms of allocation of resource blocks proposed in this work to estimate the signal-to-noise-ratio of users and set well, modulation schemes and code to be used in the LTE network.

Descrição

Citação

ABRAHAO, D. C. Alocacao de blocos de recurso em redes LTE e utilizando logica fuzzy e estimacao adaptativa de banda efetiva. 2015. 129 f. Dissertação (Mestrado em Engenharia Elétrica e da Computação) - Universidade Federal de Goiás, Goiânia, 2015.