In this article, we propose an approach for estimating delay bound on user data in the downlink of wireless multicarrier 5G networks. To this end, we propose a stochastic arrival curve based on the parameters of a lognormal beta multifractal traffic model. More specifically, we present a delay bound equation that takes into account this novel stochastic arrival curve and a stochastic service curve for multicarrier systems. Simulations are carried out to confirm that the precision of the delay bound estimation using network calculus is enhanced by considering the proposed arrival envelope and service curve.
INTRODUCTIONNew technologies have emerged to support the ever-increasing traffic rate demand related to multimedia applications. Taking this into account, techniques such as 5G modulations, massive multiple input multiple output (MIMO), etc., are being proposed, aiming greater flexibility and capacity compared to their predecessors, such as those related to 4G long term evolution (LTE) systems. 1,2 5G systems can provide high data rates and low latency through enhanced packet radio access and flexible bandwidth. Such features can be attained due to some techniques regarding data transmissions, such as filtered orthogonal frequency division multiplexing (F-OFDM) and window orthogonal frequency division multiplexing (W-OFDM). 3 Aiming to improve the quality of service (QoS) parameters, the authors in References 4 and 5 consider the allocation of resource blocks among users to eliminate interference among femtocells. For this, the authors in References 4 and 5 propose a greedy algorithm that reaches solutions close to the optimum. Other works try to improve QoS parameters applying network traffic flow rate control or congestion control mechanisms. 6 The delay and backlog are important QoS parameters to be estimated in networks, 7,8 once they provide information on the link behavior for planning and control. For example, one can determine the maximum number of users that can be accepted to the system to meet the required delay (user admission). 9 Specifically, in the 5G system, QoS parameters will play an important role, aiding the control mechanisms of the architecture to assist predetermined classes of services. 10 Network calculus is a tool that provides a deterministic and statistical estimation of QoS parameters, such as backlog and delay. 7,8,11 In fact, the maximum delay in a network, for example, can be estimated through the arrival envelope process and the service curve.Models that precisely describe network traffic flows can enhance the precision in estimating QoS parameters with network calculus. 11,12 Multifractal models present such modeling capabilities. 13 Multifractal modeling can capture network traffic behaviors such as long-range dependence and burst incidences at different time scales. 14,15 These characteristics
