Robust and Fair Multi-Objective Power Allocation Problem Based on Efficient and Healthy Cognitive Radio Article Swipe
Xiong Guo
,
Min Wang
,
Carina Cheng
,
MengChu Zhou
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.13164/re.2024.0100
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.13164/re.2024.0100
Cognitive radio networks (CRNs) is a technology that can alleviate the scarcity of radio resources, improve communication efficiency, and reduce electromagnetic radiation pollution. However, traditional research mostly concentrates on a single optimization function, which is too constrained to achieve global consideration. We suggest a multi-objective optimization problem (MOP) with the objectives of transmission rate and power efficiency. Then, we introduce a fairness factor with the minimum protection rate to ensure the quality of data transfer for each secondary user(SU). We use the ellipsoid set to characterize the uncertain parameters under the actual channel state information (CSI). In the worst case, the semi-infinite programming (SIP) problem is transformed into a second-order cone programming (SOCP) problem. The original problem is linearly combined using the weighted-sum method to construct a single objective problem (SOP), which is then turned into a solvable convex optimization problem and resolved using the Lagrange dual algorithm and sub-gradient method. The simulation results demonstrate the ability of our proposed algorithm to balance power and transmission rate optimization by adjusting the weighting values, while maintaining good robustness.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.13164/re.2024.0100
- https://doi.org/10.13164/re.2024.0100
- OA Status
- gold
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389939390
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389939390Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.13164/re.2024.0100Digital Object Identifier
- Title
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Robust and Fair Multi-Objective Power Allocation Problem Based on Efficient and Healthy Cognitive RadioWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-12-19Full publication date if available
- Authors
-
Xiong Guo, Min Wang, Carina Cheng, MengChu ZhouList of authors in order
- Landing page
-
https://doi.org/10.13164/re.2024.0100Publisher landing page
- PDF URL
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https://doi.org/10.13164/re.2024.0100Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.13164/re.2024.0100Direct OA link when available
- Concepts
-
Cognitive radio, Cognition, Power (physics), Computer science, Mathematical optimization, Mathematics, Telecommunications, Psychology, Wireless, Neuroscience, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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31Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.method | 123 |
| abstract_inverted_index.mostly | 26 |
| abstract_inverted_index.reduce | 19 |
| abstract_inverted_index.single | 30, 127 |
| abstract_inverted_index.turned | 134 |
| abstract_inverted_index.ability | 156 |
| abstract_inverted_index.achieve | 38 |
| abstract_inverted_index.balance | 162 |
| abstract_inverted_index.channel | 92 |
| abstract_inverted_index.improve | 15 |
| abstract_inverted_index.method. | 150 |
| abstract_inverted_index.minimum | 65 |
| abstract_inverted_index.problem | 46, 104, 116, 129, 140 |
| abstract_inverted_index.quality | 71 |
| abstract_inverted_index.results | 153 |
| abstract_inverted_index.suggest | 42 |
| abstract_inverted_index.values, | 172 |
| abstract_inverted_index.However, | 23 |
| abstract_inverted_index.Lagrange | 145 |
| abstract_inverted_index.combined | 119 |
| abstract_inverted_index.fairness | 61 |
| abstract_inverted_index.linearly | 118 |
| abstract_inverted_index.networks | 2 |
| abstract_inverted_index.original | 115 |
| abstract_inverted_index.problem. | 113 |
| abstract_inverted_index.proposed | 159 |
| abstract_inverted_index.research | 25 |
| abstract_inverted_index.resolved | 142 |
| abstract_inverted_index.scarcity | 11 |
| abstract_inverted_index.solvable | 137 |
| abstract_inverted_index.transfer | 74 |
| abstract_inverted_index.Cognitive | 0 |
| abstract_inverted_index.adjusting | 169 |
| abstract_inverted_index.algorithm | 147, 160 |
| abstract_inverted_index.alleviate | 9 |
| abstract_inverted_index.construct | 125 |
| abstract_inverted_index.ellipsoid | 82 |
| abstract_inverted_index.function, | 32 |
| abstract_inverted_index.introduce | 59 |
| abstract_inverted_index.objective | 128 |
| abstract_inverted_index.radiation | 21 |
| abstract_inverted_index.secondary | 77 |
| abstract_inverted_index.uncertain | 87 |
| abstract_inverted_index.user(SU). | 78 |
| abstract_inverted_index.weighting | 171 |
| abstract_inverted_index.objectives | 50 |
| abstract_inverted_index.parameters | 88 |
| abstract_inverted_index.pollution. | 22 |
| abstract_inverted_index.protection | 66 |
| abstract_inverted_index.resources, | 14 |
| abstract_inverted_index.simulation | 152 |
| abstract_inverted_index.technology | 6 |
| abstract_inverted_index.constrained | 36 |
| abstract_inverted_index.demonstrate | 154 |
| abstract_inverted_index.efficiency, | 17 |
| abstract_inverted_index.efficiency. | 56 |
| abstract_inverted_index.information | 94 |
| abstract_inverted_index.maintaining | 174 |
| abstract_inverted_index.programming | 102, 111 |
| abstract_inverted_index.robustness. | 176 |
| abstract_inverted_index.traditional | 24 |
| abstract_inverted_index.transformed | 106 |
| abstract_inverted_index.characterize | 85 |
| abstract_inverted_index.concentrates | 27 |
| abstract_inverted_index.optimization | 31, 45, 139, 167 |
| abstract_inverted_index.second-order | 109 |
| abstract_inverted_index.sub-gradient | 149 |
| abstract_inverted_index.transmission | 52, 165 |
| abstract_inverted_index.weighted-sum | 122 |
| abstract_inverted_index.communication | 16 |
| abstract_inverted_index.semi-infinite | 101 |
| abstract_inverted_index.consideration. | 40 |
| abstract_inverted_index.electromagnetic | 20 |
| abstract_inverted_index.multi-objective | 44 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5110793713 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I4385474403 |
| citation_normalized_percentile.value | 0.23449545 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |