Adaptive fuzzy flow rate control considering multifractal traffic modeling and 5G communications


Autoři: Alisson Assis Cardoso aff001;  Flávio Henrique Teles Vieira aff001
Působiště autorů: School of Mechanical, Electrical and Computer Engineering, Federal University of Goiás, Goiânia, Goiás, Brazil aff001
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224883

Souhrn

In this paper, we propose a predictive Generalized OBF (Orthonormal Basis Functions)-Fuzzy flow control scheme for the 5G downlink by deriving an expression for the optimal control rate of the traffic sources considering minimization of data delay and a minimum traffic rate to the users. The adaptive GOBF-Fuzzy model is applied to predict queueing behavior in initial 5G systems. To this end, we propose to obtain orthonormal basis functions related to the real traffic flows via multifractal modeling, inserting these functions into the fuzzy model trained with the LMS (Least Mean Square) adaptive algorithm. Simulations of a F-OFDM (Filtered Orthogonal Frequency Division Multiplexing) based 5G Downlink are carried out to validate the proposed flow control algorithm. Comparisons with other predictive control schemes in the literature prove the efficiency of the adaptive GOBF-fuzzy based control in enhancing the performance of the system downlink as well as guaranteeing some QoS (Quality of Service) parameters.

Klíčová slova:

Algorithms – Antennas – Flow rate – Network analysis – Random variables – Signal bandwidth – Multiplexing


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Článek vyšel v časopise

PLOS One


2019 Číslo 11