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Throughput Maximization for Multiple D2D Group Communications Underlaying Cellular Networks
In the scenario where multiple device-to-device (D2D) users and cellular users coexist, the large number of D2D users not only results in the shortage of spectrum resources but also brings interference to the communication of cellular users. In this paper, we establish a clustering model centered on...
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Published in: | Wireless communications and mobile computing 2020, Vol.2020 (2020), p.1-10 |
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description | In the scenario where multiple device-to-device (D2D) users and cellular users coexist, the large number of D2D users not only results in the shortage of spectrum resources but also brings interference to the communication of cellular users. In this paper, we establish a clustering model centered on cellular users and propose a resource allocation algorithm based on a D2D clustering model. On the basis of ensuring the throughput requirements of cellular users, this algorithm reconstructs various matrices in the graph theory through probability models, sets the priority of D2D pairs, and maximizes the number of user accesses under interference tolerance. Besides, on the optimization of the number of users, we adopt the Rubinstein game model to adjust the game order according to the priority and optimize the bandwidth allocation mode, so as to improve the overall throughput of the network. Simulation results show that the proposed algorithm can increase the number of users and the network throughput, while shortening the spectrum allocation time by more than half. |
doi_str_mv | 10.1155/2020/8833579 |
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In this paper, we establish a clustering model centered on cellular users and propose a resource allocation algorithm based on a D2D clustering model. On the basis of ensuring the throughput requirements of cellular users, this algorithm reconstructs various matrices in the graph theory through probability models, sets the priority of D2D pairs, and maximizes the number of user accesses under interference tolerance. Besides, on the optimization of the number of users, we adopt the Rubinstein game model to adjust the game order according to the priority and optimize the bandwidth allocation mode, so as to improve the overall throughput of the network. Simulation results show that the proposed algorithm can increase the number of users and the network throughput, while shortening the spectrum allocation time by more than half.</description><identifier>ISSN: 1530-8669</identifier><identifier>EISSN: 1530-8677</identifier><identifier>DOI: 10.1155/2020/8833579</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Cellular communication ; Clustering ; Communication ; Game theory ; Graph theory ; Impact factors ; Interference ; Optimization ; Public safety ; Resource allocation ; Spectrum allocation ; User requirements ; Utility functions</subject><ispartof>Wireless communications and mobile computing, 2020, Vol.2020 (2020), p.1-10</ispartof><rights>Copyright © 2020 Ji-Ai He et al.</rights><rights>Copyright © 2020 Ji-Ai He et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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Simulation results show that the proposed algorithm can increase the number of users and the network throughput, while shortening the spectrum allocation time by more than half.</description><subject>Algorithms</subject><subject>Cellular communication</subject><subject>Clustering</subject><subject>Communication</subject><subject>Game theory</subject><subject>Graph theory</subject><subject>Impact factors</subject><subject>Interference</subject><subject>Optimization</subject><subject>Public safety</subject><subject>Resource allocation</subject><subject>Spectrum allocation</subject><subject>User requirements</subject><subject>Utility functions</subject><issn>1530-8669</issn><issn>1530-8677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqF0D1PwzAQgGELgUQpbMzIEiOE2s6H4xGlUJBaWMrEENnJuXVJ4uAkKuXXkxIEI9Pd8OhOehE6p-SG0jCcMMLIJI59P-TiAI1o6BMvjjg__N0jcYxOmmZDCPEJoyP0ulw7263WddfihfwwpfmUrbEV1tbhRVe0pi4AT9kUz3pX48SWZVeZ7Bs1-KXKwRVyZ6oVTqAoukI6_ATt1rq35hQdaVk0cPYzx2h5f7dMHrz58-wxuZ17mR-R1lNcB4KrjNEcVCxAKEWzDCAWGeRKqFhHihJOCUSacEZ4wCgjIGLQOgiJP0aXw9na2fcOmjbd2M5V_ceUBSHlIRN9kzG6HlTmbNM40GntTCndLqUk3ddL9_XSn3o9vxr42lS53Jr_9MWgoTeg5Z9mNIiC0P8CQjJ6DQ</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Chen, Wei</creator><creator>Xu, Lei</creator><creator>Jia, Lu</creator><creator>He, Ji-Ai</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0003-2510-4984</orcidid><orcidid>https://orcid.org/0000-0002-1184-1652</orcidid><orcidid>https://orcid.org/0000-0001-9227-5324</orcidid></search><sort><creationdate>2020</creationdate><title>Throughput Maximization for Multiple D2D Group Communications Underlaying Cellular Networks</title><author>Chen, Wei ; 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subjects | Algorithms Cellular communication Clustering Communication Game theory Graph theory Impact factors Interference Optimization Public safety Resource allocation Spectrum allocation User requirements Utility functions |
title | Throughput Maximization for Multiple D2D Group Communications Underlaying Cellular Networks |
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