Spectrum pricing for cognitive radio networks with user’s stochastic distribution

Amid the dynamic spectrum access in cognitive radio networks, when complex spectrum conditions should be taken into account, how to price the spectrum in order to benefit primary systems in maximization is still under-investigated. In this paper, we devise a spectrum pricing method to address this i...

Full description

Saved in:
Bibliographic Details
Main Authors: Wang, Li, Lam, Kwok-Yan, Xiong, Mudi, Li, Feng, Liu, Xin, Wang, Jian
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/137332
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-137332
record_format dspace
spelling sg-ntu-dr.10356-1373322020-03-18T04:07:36Z Spectrum pricing for cognitive radio networks with user’s stochastic distribution Wang, Li Lam, Kwok-Yan Xiong, Mudi Li, Feng Liu, Xin Wang, Jian School of Computer Science and Engineering Engineering::Computer science and engineering Cognitive Radio Spectrum Allocation Amid the dynamic spectrum access in cognitive radio networks, when complex spectrum conditions should be taken into account, how to price the spectrum in order to benefit primary systems in maximization is still under-investigated. In this paper, we devise a spectrum pricing method to address this issue in cognitive networks. In our proposed mechanism, leasing spectrum is collected for uniform selling and classified into three kinds of channels—high-quality channel, mid-quality channel and low-quality channel, respectively. They will be priced variously according to different interference characteristics caused by versatile path fading and user positions. In respond to heterogeneous channel qualities, secondary users also have own selection preferences. They can purchase one kind of channel for usage in based of channel quality and available budget. Then, we obtain the final pricing solution which is an iterative algorithm converging to a fixed point. Also, the existence of a pure Nash equilibrium is discussed to ensure the rationality of the method. In numerical results, we evaluate the effects of this proposal in spectrum pricing and primary systems’ profits. Accepted version 2020-03-18T04:07:36Z 2020-03-18T04:07:36Z 2018 Journal Article Wang, L., Lam, K.-Y., Xiong, M., Li, F., Liu, X., & Wang, J. (2019). Spectrum pricing for cognitive radio networks with user’s stochastic distribution. Wireless Networks, 25(4), 2091-2099. doi:10.1007/s11276-018-1799-8 1022-0038 https://hdl.handle.net/10356/137332 10.1007/s11276-018-1799-8 2-s2.0-85049998002 4 25 2091 2099 en Wireless Networks This is a post-peer-review, pre-copyedit version of an article published in Wireless Networks. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11276-018-1799-8 application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Cognitive Radio
Spectrum Allocation
spellingShingle Engineering::Computer science and engineering
Cognitive Radio
Spectrum Allocation
Wang, Li
Lam, Kwok-Yan
Xiong, Mudi
Li, Feng
Liu, Xin
Wang, Jian
Spectrum pricing for cognitive radio networks with user’s stochastic distribution
description Amid the dynamic spectrum access in cognitive radio networks, when complex spectrum conditions should be taken into account, how to price the spectrum in order to benefit primary systems in maximization is still under-investigated. In this paper, we devise a spectrum pricing method to address this issue in cognitive networks. In our proposed mechanism, leasing spectrum is collected for uniform selling and classified into three kinds of channels—high-quality channel, mid-quality channel and low-quality channel, respectively. They will be priced variously according to different interference characteristics caused by versatile path fading and user positions. In respond to heterogeneous channel qualities, secondary users also have own selection preferences. They can purchase one kind of channel for usage in based of channel quality and available budget. Then, we obtain the final pricing solution which is an iterative algorithm converging to a fixed point. Also, the existence of a pure Nash equilibrium is discussed to ensure the rationality of the method. In numerical results, we evaluate the effects of this proposal in spectrum pricing and primary systems’ profits.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Wang, Li
Lam, Kwok-Yan
Xiong, Mudi
Li, Feng
Liu, Xin
Wang, Jian
format Article
author Wang, Li
Lam, Kwok-Yan
Xiong, Mudi
Li, Feng
Liu, Xin
Wang, Jian
author_sort Wang, Li
title Spectrum pricing for cognitive radio networks with user’s stochastic distribution
title_short Spectrum pricing for cognitive radio networks with user’s stochastic distribution
title_full Spectrum pricing for cognitive radio networks with user’s stochastic distribution
title_fullStr Spectrum pricing for cognitive radio networks with user’s stochastic distribution
title_full_unstemmed Spectrum pricing for cognitive radio networks with user’s stochastic distribution
title_sort spectrum pricing for cognitive radio networks with user’s stochastic distribution
publishDate 2020
url https://hdl.handle.net/10356/137332
_version_ 1681046700105400320