Open AccessFinite‐state Markov modelling for wireless cooperative networks
Author(s) -
Luo Yuanqian,
Zhang Ruonan,
Cai Lin,
Xiang Siyuan
Publication year - 2014
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
eISSN - 2047-4962
pISSN - 2047-4954
DOI - 10.1049/iet-net.2013.0045
Subject(s) - computer science , fading , markov chain , wireless network , wireless , cooperative diversity , path (computing) , markov model , maximal ratio combining , signal to noise ratio (imaging) , scalability , diversity combining , computer network , channel (broadcasting) , machine learning , telecommunications , database
Finite‐state Markov chain (FSMC) models can capture the essence of time‐varying fading channels and they are important tools for wireless network protocol design and performance study. How to build FSMC models for multi‐hop and multi‐path wireless systems remains an open issue. In this study, the FSMC models are developed for amplify‐and‐forward (AF) cooperative systems with selection combining (SC) and maximum ratio combining (MRC) techniques, respectively. First, the second‐order statistics, the level‐crossing rate and the average fade duration, are derived based on the statistical properties of each individual path, for the AF cooperative systems with SC and MRC, respectively. The results reveal that, in addition to improving the average received signal‐to‐noise ratio, the diversity combining schemes also improve its second‐order statistical properties. Simulation results are given to verify the accuracy of the developed FSMC models. Finally, the models are used to optimise the configuration for scalable video streaming in an AF cooperative network. Experimental results show the feasibility and advantage of applying the proposed FSMC models for assisting protocol design and optimisation in wireless cooperative networks.