Opportunistic Spectrum Access in Self-Similar Primary Traffic

We take a stochastic optimization approach to opportunity tracking and access in self-similar primary traffic. Based on a multiple time-scale hierarchical Markovian model, we formulate opportunity tracking and access in self-similar primary traffic as a Partially Observable Markov Decision Process....

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Bibliographic Details
Main Authors: Xiangyang Xiao, Qing Zhao, Keqin Liu
Format: Article
Language:English
Published: SpringerOpen 2009-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://dx.doi.org/10.1155/2009/762547
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spelling doaj-c7a4eaead90c4a56a9c858600796b4172020-11-24T21:22:35ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802009-01-01200910.1155/2009/762547Opportunistic Spectrum Access in Self-Similar Primary TrafficXiangyang XiaoQing ZhaoKeqin LiuWe take a stochastic optimization approach to opportunity tracking and access in self-similar primary traffic. Based on a multiple time-scale hierarchical Markovian model, we formulate opportunity tracking and access in self-similar primary traffic as a Partially Observable Markov Decision Process. We show that for independent and stochastically identical channels under certain conditions, the myopic sensing policy has a simple round-robin structure that obviates the need to know the channel parameters; thus it is robust to channel model mismatch and variations. Furthermore, the myopic policy achieves comparable performance as the optimal policy that requires exponential complexity and assumes full knowledge of the channel model. http://dx.doi.org/10.1155/2009/762547
collection DOAJ
language English
format Article
sources DOAJ
author Xiangyang Xiao
Qing Zhao
Keqin Liu
spellingShingle Xiangyang Xiao
Qing Zhao
Keqin Liu
Opportunistic Spectrum Access in Self-Similar Primary Traffic
EURASIP Journal on Advances in Signal Processing
author_facet Xiangyang Xiao
Qing Zhao
Keqin Liu
author_sort Xiangyang Xiao
title Opportunistic Spectrum Access in Self-Similar Primary Traffic
title_short Opportunistic Spectrum Access in Self-Similar Primary Traffic
title_full Opportunistic Spectrum Access in Self-Similar Primary Traffic
title_fullStr Opportunistic Spectrum Access in Self-Similar Primary Traffic
title_full_unstemmed Opportunistic Spectrum Access in Self-Similar Primary Traffic
title_sort opportunistic spectrum access in self-similar primary traffic
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2009-01-01
description We take a stochastic optimization approach to opportunity tracking and access in self-similar primary traffic. Based on a multiple time-scale hierarchical Markovian model, we formulate opportunity tracking and access in self-similar primary traffic as a Partially Observable Markov Decision Process. We show that for independent and stochastically identical channels under certain conditions, the myopic sensing policy has a simple round-robin structure that obviates the need to know the channel parameters; thus it is robust to channel model mismatch and variations. Furthermore, the myopic policy achieves comparable performance as the optimal policy that requires exponential complexity and assumes full knowledge of the channel model.
url http://dx.doi.org/10.1155/2009/762547
work_keys_str_mv AT xiangyangxiao opportunisticspectrumaccessinselfsimilarprimarytraffic
AT qingzhao opportunisticspectrumaccessinselfsimilarprimarytraffic
AT keqinliu opportunisticspectrumaccessinselfsimilarprimarytraffic
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