Open AccessWireless channel model using stochastic high‐level Petri nets for cross‐layer performance analysis in orthogonal frequency‐division multiplexing system
Author(s) -
Lei Lei,
Wang Huijian,
Lin Chuang,
Zhong Zhangdui
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2014.0394
Subject(s) - orthogonal frequency division multiplexing , computer science , channel (broadcasting) , wireless , multiplexing , petri net , stochastic petri net , state space , markov process , markov model , markov chain , wireless network , algorithm , throughput , computer network , mathematics , telecommunications , statistics , machine learning
In this study, the authors form a wireless channel model for orthogonal frequency‐division multiplexing (OFDM) systems with stochastic high‐level Petri net (SHLPN) formalism in order to simplify the cross‐layer performance analysis of modern wireless systems. Compared with existing finite state Markov channel model whose state space grows exponentially with the number of OFDM subchannels, the author's proposed SHLPN model uses state aggregation technique to deal with this problem. Closed‐form expressions to calculate the transition probabilities among the compound markings of the SHLPN model are provided. When applied to derive the performance measures for OFDM system in terms of the average throughput, average delay and packet dropping probability, the SHLPN model can accurately capture the correlated time‐varying nature of wireless channels. Simulation is performed to show that the numerical results offered by the proposed model are more accurate compared with other simplified channel models for avoiding state space complexity.