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Estimation of quality of service parameters for OFDM–TDMA networks using Markov chains and service curve
Author(s) -
Vieira Flávio H. T.,
Costa Victor H. T.,
Rocha Flávio G. C.,
Ling Lee L.
Publication year - 2017
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3125
Subject(s) - time division multiple access , computer science , orthogonal frequency division multiplexing , queueing theory , quality of service , markov process , computer network , markov chain , markov model , autocorrelation , real time computing , mathematics , statistics , channel (broadcasting) , machine learning
Summary This paper presents a model based on Queueing Theory for Orthogonal Frequency‐Division Multiplexing–Time‐Division Multiple Access (OFDM–TDMA) networks. This network model requires a Markovian model to the traffic processes. Thus, we present a Markov Modulated Fluid Model (MMFM) with autocorrelation function fitting for the network traffic, in order to evaluate the performance of the transmission link in OFDM–TDMA systems. That is, we deduce equations for estimating QoS parameters of OFDM–TDMA systems. The obtained results confirm that the proposed network model is efficient in describing the OFDM based link performance. A novel equation is also introduced for estimating the buffer overflow probability in OFDM–TDMA systems using a proposed network service curve. The computational effort is reduced compared to the Queueing Theory based method of overflow probability estimation. Besides, the results show that the estimates are very close to those obtained by simulations.