Dynamic bandwidth allocation for OFDMA-PONs using Hidden Markov Model

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4 Citations (Scopus)
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Accurate prediction of traffic conditions on OFDMA-PONs is important because of its vital role in network resource management and efficient bandwidth allocation. Given the dynamic and stochastic nature of network traffic, our proposed algorithm conducts a probabilistic approach by using the Hidden Markov Model (HMM). The HMM defines traffic states with two parameters: the mean and contrast of the bandwidth request observations. Simulation results demonstrate the performance comparison between with and without the prediction method in terms of throughput and end-to-end delay. As a result, the throughput improves 15% and the saturation offered load of the delay for the prediction and non-prediction is 0.8 and 0.7, respectively.
Original languageEnglish
Pages (from-to)2169-3536
JournalIEEE Access
Early online date2 Feb 2017
Publication statusPublished - 25 Oct 2017


  • dynamic bandwidth allocation
  • Hidden Markov Model


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