Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks
The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Altho...
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doaj-cf34e40f0145459d97877ed018a3d5cc2020-11-24T23:01:13ZengMDPI AGSensors1424-82202018-05-01185150010.3390/s18051500s18051500Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell NetworksShashi Shah0Somsak Kittipiyakul1Yuto Lim2Yasuo Tan3School of Information, Computer, and Communication Technology, Sirindhorn International Institute of Technology (SIIT), Thammasat University (TU), Pathum Thani 12121, ThailandSchool of Information, Computer, and Communication Technology, Sirindhorn International Institute of Technology (SIIT), Thammasat University (TU), Pathum Thani 12121, ThailandSchool of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Ishikawa 923-1292, JapanSchool of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Ishikawa 923-1292, JapanThe paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.http://www.mdpi.com/1424-8220/18/5/1500small cellsdistributed subchannel allocationgame theorybest-responsepotential gamesmarginal contribution |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shashi Shah Somsak Kittipiyakul Yuto Lim Yasuo Tan |
spellingShingle |
Shashi Shah Somsak Kittipiyakul Yuto Lim Yasuo Tan Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks Sensors small cells distributed subchannel allocation game theory best-response potential games marginal contribution |
author_facet |
Shashi Shah Somsak Kittipiyakul Yuto Lim Yasuo Tan |
author_sort |
Shashi Shah |
title |
Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks |
title_short |
Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks |
title_full |
Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks |
title_fullStr |
Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks |
title_full_unstemmed |
Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks |
title_sort |
marginal contribution-based distributed subchannel allocation in small cell networks |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-05-01 |
description |
The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics. |
topic |
small cells distributed subchannel allocation game theory best-response potential games marginal contribution |
url |
http://www.mdpi.com/1424-8220/18/5/1500 |
work_keys_str_mv |
AT shashishah marginalcontributionbaseddistributedsubchannelallocationinsmallcellnetworks AT somsakkittipiyakul marginalcontributionbaseddistributedsubchannelallocationinsmallcellnetworks AT yutolim marginalcontributionbaseddistributedsubchannelallocationinsmallcellnetworks AT yasuotan marginalcontributionbaseddistributedsubchannelallocationinsmallcellnetworks |
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1725640290400731136 |