Spectrum sharing for heterogeneous networks and application systems in TV white spaces

In 2010, federal communications commission released the final ruling to allow the unlicensed operation of TV white spaces, i.e., locally vacant TV channels. Since TV white spaces are open to all networks and all types of applications, it is likely that there will be multiple networks and application...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhang, Wenjie, Zhang, Guanglin, Zheng, Yifeng, Yang, Liwei, Yeo, Chai Kiat
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/87530
http://hdl.handle.net/10220/45456
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-87530
record_format dspace
spelling sg-ntu-dr.10356-875302020-03-07T11:48:58Z Spectrum sharing for heterogeneous networks and application systems in TV white spaces Zhang, Wenjie Zhang, Guanglin Zheng, Yifeng Yang, Liwei Yeo, Chai Kiat School of Computer Science and Engineering Spectrum Sharing Heterogeneous Systems In 2010, federal communications commission released the final ruling to allow the unlicensed operation of TV white spaces, i.e., locally vacant TV channels. Since TV white spaces are open to all networks and all types of applications, it is likely that there will be multiple networks and application systems authorized to use the same TV channels at the same time. Currently, there is mechanism for different users to operate in the TV white spaces within one system, while TV spectrum sharing among heterogeneous networks and application systems is largely ignored. To address the problem, this paper designs a trading mechanism to study the TV spectrum market between Geolocation database and heterogeneous application systems. We formulate the spectrum sharing problem into a 0-1 integer optimization problem and prove that this problem is NP-complete. The proposed solution decomposes an optimal fractional solution of a NP-hard problem into a convex combination of internal solutions by randomized rounding algorithm. Simulation results show that the proposed approximation algorithm can achieve a close-to-optimal solution with far less complexity. Published version 2018-08-03T08:15:12Z 2019-12-06T16:43:51Z 2018-08-03T08:15:12Z 2019-12-06T16:43:51Z 2018 Journal Article Zhang, W., Zhang, G., Zheng, Y., Yang, L., & Yeo, C. K. (2018). Spectrum sharing for heterogeneous networks and application systems in TV white spaces. IEEE Access, 6, 19833-19843. https://hdl.handle.net/10356/87530 http://hdl.handle.net/10220/45456 10.1109/ACCESS.2018.2824836 en IEEE Access © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 11 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Spectrum Sharing
Heterogeneous Systems
spellingShingle Spectrum Sharing
Heterogeneous Systems
Zhang, Wenjie
Zhang, Guanglin
Zheng, Yifeng
Yang, Liwei
Yeo, Chai Kiat
Spectrum sharing for heterogeneous networks and application systems in TV white spaces
description In 2010, federal communications commission released the final ruling to allow the unlicensed operation of TV white spaces, i.e., locally vacant TV channels. Since TV white spaces are open to all networks and all types of applications, it is likely that there will be multiple networks and application systems authorized to use the same TV channels at the same time. Currently, there is mechanism for different users to operate in the TV white spaces within one system, while TV spectrum sharing among heterogeneous networks and application systems is largely ignored. To address the problem, this paper designs a trading mechanism to study the TV spectrum market between Geolocation database and heterogeneous application systems. We formulate the spectrum sharing problem into a 0-1 integer optimization problem and prove that this problem is NP-complete. The proposed solution decomposes an optimal fractional solution of a NP-hard problem into a convex combination of internal solutions by randomized rounding algorithm. Simulation results show that the proposed approximation algorithm can achieve a close-to-optimal solution with far less complexity.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Zhang, Wenjie
Zhang, Guanglin
Zheng, Yifeng
Yang, Liwei
Yeo, Chai Kiat
format Article
author Zhang, Wenjie
Zhang, Guanglin
Zheng, Yifeng
Yang, Liwei
Yeo, Chai Kiat
author_sort Zhang, Wenjie
title Spectrum sharing for heterogeneous networks and application systems in TV white spaces
title_short Spectrum sharing for heterogeneous networks and application systems in TV white spaces
title_full Spectrum sharing for heterogeneous networks and application systems in TV white spaces
title_fullStr Spectrum sharing for heterogeneous networks and application systems in TV white spaces
title_full_unstemmed Spectrum sharing for heterogeneous networks and application systems in TV white spaces
title_sort spectrum sharing for heterogeneous networks and application systems in tv white spaces
publishDate 2018
url https://hdl.handle.net/10356/87530
http://hdl.handle.net/10220/45456
_version_ 1681034362679721984