Alocação de Blocos de Recurso em Redes LTE com Estimativa de Limitante de Retardo através de Cálculo de Rede

Abstract

Resumo-Neste artigoé proposto um algoritmo de alocação de blocos de recurso para sistemas de comunicação LTE (Long Term Evolution) que considera o limitante de retardo estimado através de Cálculo de Rede utilizando curva de serviço e processo envelope MFBAP (Multifractal Bounded Arrival Process) para decidir sobre a alocação de recursos de rádio disponíveis. São realizadas comparações com outros algoritmos de alocação através de parâmetros de QoS (Quality of Service) como retardo médio, vazão total, tempo de processamento, taxa de perda é ındice de justiça (fairness), comprovando a eficiência do algoritmo proposto.Palavras-Chave-LTE, Escalonamento, Retardo, Cálculo de Rede.Abstract-In this paper it is proposed an algorithm to allocate resource blocks for LTE (Long Term Evolution) communication systems which considers the delay target estimated through Network Calculus using service curve and MFBAP (Multifractal Bounded Arrival Process) envelope process in order to decide on the scheduling of available radio resources. Comparisons with other allocation algorithms are carried out through QoS (Quality of Service) parameters such as average delay, total throughput, processing time, loss rate and fairness index, proving the efficiency of the proposed algorithm.

Resource scheduling scheme for 5G mmWave CP‐OFDM based wireless networks with delay and power allocation optimizations

“…We developed the simulations by comparing the results of the proposed algorithm with those of the following resource allocation algorithms: the QoS‐guaranteed algorithm [5]; a delay estimation algorithm [7], namely, Est‐delay; a delay and throughput optimization algorithm [9], namely, Opt‐delay; and an EP‐based algorithm [11]. We also compared the throughput provided by the algorithms with an upper bound that comprises the throughput value obtained by solving the throughput optimization problem given by Equations (38)–(40) and finding the optimal value for the weight vector through exhaustive searching.…”

“…The simulations were developed based on the parameters for a downlink transmission scenario presented in Table 2, which are similar to the values in previous references [5–9, 17, 18, 30, 31]. The bit rate and MCS index associated with the SNR are defined with the 4‐bit Channel Quality Indicator using Quadrature Phase Shift Keying (QPSK), 16‐QAM, 64‐QAM, and 256‐QAM modulations according to the mapping presented in 3GPP [15].…”

“…In Ferreirat and others [7], the Est‐delay algorithm, which considered the system‐estimated delay information, channel quality, and the maximum delay value for each user and selected the scheduling of available resources, was presented. It was compared with other algorithms from the literature using statistical data regarding QoS parameters, and its efficiency was proven.…”

“…This article focuses on an approach for resource scheduling in wireless networks. Allocation schemes, such as those presented in previous studies [5][6][7][8][9] and others not discussed here, aim to apply optimization algorithms to satisfy Quality of Service (QoS) requirements (e.g., regarding delay, throughput, fairness, and goodput [GP]). In the resource allocation context, delay is considered an essential QoS parameter, especially for real-time applications with variable transmission rates and specified bandwidth requirements, such as video and videoconferencing services.…”

“…In Su and others [6], an algorithm based on the Particle Swarm Optimization heuristic was proposed for maximizing the total system throughput. In Ferreira and others [7], an algorithm that used the estimated network delay information to reduce the system delay parameter was proposed. In Zhou and Wunder [9], contrary to our proposed approach, a network delay optimization algorithm that used idle state prediction and considered the default Modulation and Coding Scheme (MCS) of LTE networks was proposed.…”