Distributed Bargaining Mechanisms for MIMO Dynamic Spectrum Access Systems

Nguyen, DN; Krunz, M; Hanly, SV

Distributed Bargaining Mechanisms for MIMO Dynamic Spectrum Access Systems

Nguyen, DN

Krunz, M Hanly, SV

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Cognitive Communications and Networking, 2015, 1 (1), pp. 113 - 127
Issue Date:: 2015-03-01

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Field	Value	Language
dc.contributor.author	Nguyen, DN https://orcid.org/0000-0003-2659-8648	en_US
dc.contributor.author	Krunz, M	en_US
dc.contributor.author	Hanly, SV	en_US
dc.date.issued	2015-03-01	en_US
dc.identifier.citation	IEEE Transactions on Cognitive Communications and Networking, 2015, 1 (1), pp. 113 - 127	en_US
dc.identifier.uri	http://hdl.handle.net/10453/117238
dc.description.abstract	© 2015 IEEE. Dynamic spectrum access (DSA) and MIMO communications are among the most promising solutions to address the ever increasing wireless traffic demand. An integration that successfully embraces the two is far from trivial due to the dynamics of spectrum opportunities as well as the requirement to jointly optimize both spectrum allocation and spatial/antenna pattern in a distributed fashion. Regardless of spectrum dynamics and heterogeneity, existing literature on channel/power allocation in MIMO DSA systems is only applicable to centralized cases. Our objective here is to design distributed algorithms that jointly allocate opportunistic channels to various links and to simultaneously optimize the MIMO precoding matrices so as to achieve fairness or maximize network throughput. For self-interested DSA links, our distributed algorithm allows links to negotiate channel allocation based on Nash bargaining (NB) and configure the precoding matrices so that links' rate demands are guaranteed while the surplus resources (after meeting minimum rate demands) are fairly allocated. Next, we consider a network throughput maximization formulation (NET-MAX). Both the NB-based and NET-MAX problems are combinatorial with mixed variables. To tackle them, we first transform the original problems by incorporating the concept of timesharing. Using dual decomposition, we develop optimal distributed algorithms for timesharing case, which shed light on how to derive a distributed algorithm for the original problems. Our work fills a gap in the literature of channel allocation where a central controller is not available.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DE150101092
dc.relation.ispartof	IEEE Transactions on Cognitive Communications and Networking	en_US
dc.relation.isbasedon	10.1109/TCCN.2015.2496317	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Distributed Bargaining Mechanisms for MIMO Dynamic Spectrum Access Systems	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

© 2015 IEEE. Dynamic spectrum access (DSA) and MIMO communications are among the most promising solutions to address the ever increasing wireless traffic demand. An integration that successfully embraces the two is far from trivial due to the dynamics of spectrum opportunities as well as the requirement to jointly optimize both spectrum allocation and spatial/antenna pattern in a distributed fashion. Regardless of spectrum dynamics and heterogeneity, existing literature on channel/power allocation in MIMO DSA systems is only applicable to centralized cases. Our objective here is to design distributed algorithms that jointly allocate opportunistic channels to various links and to simultaneously optimize the MIMO precoding matrices so as to achieve fairness or maximize network throughput. For self-interested DSA links, our distributed algorithm allows links to negotiate channel allocation based on Nash bargaining (NB) and configure the precoding matrices so that links' rate demands are guaranteed while the surplus resources (after meeting minimum rate demands) are fairly allocated. Next, we consider a network throughput maximization formulation (NET-MAX). Both the NB-based and NET-MAX problems are combinatorial with mixed variables. To tackle them, we first transform the original problems by incorporating the concept of timesharing. Using dual decomposition, we develop optimal distributed algorithms for timesharing case, which shed light on how to derive a distributed algorithm for the original problems. Our work fills a gap in the literature of channel allocation where a central controller is not available.

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http://hdl.handle.net/10453/117238