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Joint Rate and Fairness Improvement Based on Adaptive Weighted Graph Matrix for Uplink SCMA with Randomly Distributed Users
Cheraghy, Maryam1; Chen, Wen1; Tang, Hongying2; Wu, Qingqing3; Li, Jun4
2021-05-01
Source PublicationIEEE Transactions on Communications
ISSN0090-6778
Volume69Issue:5Pages:3106-3118
Abstract

Developing resource allocation algorithms for the uplink sparse code multiple access (SCMA) scheme to satisfy multiple objectives is challenging, especially where users are randomly distributed. In this paper, we aim to address this challenge by developing a joint resource allocation method as a multi-objective optimization (MO) problem to maximize the average sum rate and fairness among users as key and sub-key objectives, respectively. For this purpose, the exact analytical expressions for the average sum rate and users' individual rate are extracted based on an adaptive weighted graph matrix (AWGM). An AWGM matrix beneficially replaces the factor graph and the power allocation matrices to simplify the MO problem based on the asymmetric modified bipartite matching (AMBM) algorithm. The power allocation strategy is utilized during the optimal resource assignment process using the AMBM algorithm. After the AMBM process, we propose a low-complexity four-step algorithm to obtain the AWGM. The simulation results show that our proposed method can compromise and improve the multiple objectives' performance and guarantees a stable range of network performance at different times.

KeywordAsymmetric Bipartite Matching Multi-objective Optimization Randomly Deployed Users Resource Allocation Sparse Code Multiple Access
DOI10.1109/TCOMM.2021.3058529
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Telecommunications
WOS SubjectEngineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000652065300025
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141
Scopus ID2-s2.0-85101451199
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Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorChen, Wen
Affiliation1.Department of Electronic Engineering, SICS, Shanghai Jiao Tong University, Shanghai, 200240, China
2.Institute of Microsystems and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
3.Department of Electrical and Computer Engineering, University of Macau, Taipa, 117576, Macao
4.School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
Recommended Citation
GB/T 7714
Cheraghy, Maryam,Chen, Wen,Tang, Hongying,et al. Joint Rate and Fairness Improvement Based on Adaptive Weighted Graph Matrix for Uplink SCMA with Randomly Distributed Users[J]. IEEE Transactions on Communications, 2021, 69(5), 3106-3118.
APA Cheraghy, Maryam., Chen, Wen., Tang, Hongying., Wu, Qingqing., & Li, Jun (2021). Joint Rate and Fairness Improvement Based on Adaptive Weighted Graph Matrix for Uplink SCMA with Randomly Distributed Users. IEEE Transactions on Communications, 69(5), 3106-3118.
MLA Cheraghy, Maryam,et al."Joint Rate and Fairness Improvement Based on Adaptive Weighted Graph Matrix for Uplink SCMA with Randomly Distributed Users".IEEE Transactions on Communications 69.5(2021):3106-3118.
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