Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2311.04546
Weighted sum-rate (WSR) maximization plays a critical role in communication system design. This paper examines three optimization methods for WSR maximization, which ensure convergence to stationary points: two block coordinate ascent (BCA) algorithms, namely, weighted sum-minimum mean-square error (WMMSE) and WSR maximization via fractional programming (WSR-FP), along with a minorization-maximization (MM) algorithm, WSR maximization via MM (WSR-MM). Our contributions are threefold. Firstly, we delineate the exact relationships among WMMSE, WSR-FP, and WSR-MM, which, despite their extensive use in the literature, lack a comprehensive comparative study. By probing the theoretical underpinnings linking the BCA and MM algorithmic frameworks, we reveal the direct correlations between the equivalent transformation techniques, essential to the development of WMMSE and WSR-FP, and the surrogate functions pivotal to WSR-MM. Secondly, we propose a novel algorithm, WSR-MM+, harnessing the flexibility of selecting surrogate functions in MM framework. By circumventing the repeated matrix inversions in the search for optimal Lagrange multipliers in existing algorithms, WSR-MM+ significantly reduces the computational load per iteration and accelerates convergence. Thirdly, we reconceptualize WSR-MM+ within the BCA framework, introducing a new equivalent transform, which gives rise to an enhanced version of WSR-FP, named as WSR-FP+. We further demonstrate that WSR-MM+ can be construed as the basic gradient projection method. This perspective yields a deeper understanding into its computational intricacies. Numerical simulations corroborate the connections between WMMSE, WSR-FP, and WSR-MM and confirm the efficacy of the proposed WSR-MM+ and WSR-FP+ algorithms.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2311.04546
- https://arxiv.org/pdf/2311.04546
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388555588
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388555588Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2311.04546Digital Object Identifier
- Title
-
Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in CommunicationsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-11-08Full publication date if available
- Authors
-
Zepeng Zhang, Ziping Zhao, Kaiming Shen, Daniel P. Palomar, Wei YuList of authors in order
- Landing page
-
https://arxiv.org/abs/2311.04546Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2311.04546Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2311.04546Direct OA link when available
- Concepts
-
Maximization, Algorithm, Flexibility (engineering), Convergence (economics), Mathematics, Perspective (graphical), Mathematical optimization, Block (permutation group theory), Computer science, Transformation (genetics), Statistics, Combinatorics, Artificial intelligence, Chemistry, Economic growth, Economics, Biochemistry, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.WSR-MM, | 71 |
| abstract_inverted_index.WSR-MM. | 121 |
| abstract_inverted_index.between | 102, 220 |
| abstract_inverted_index.confirm | 226 |
| abstract_inverted_index.design. | 11 |
| abstract_inverted_index.despite | 73 |
| abstract_inverted_index.further | 192 |
| abstract_inverted_index.linking | 90 |
| abstract_inverted_index.method. | 204 |
| abstract_inverted_index.methods | 17 |
| abstract_inverted_index.namely, | 33 |
| abstract_inverted_index.optimal | 149 |
| abstract_inverted_index.pivotal | 119 |
| abstract_inverted_index.points: | 26 |
| abstract_inverted_index.probing | 86 |
| abstract_inverted_index.propose | 124 |
| abstract_inverted_index.reduces | 157 |
| abstract_inverted_index.version | 185 |
| abstract_inverted_index.Firstly, | 61 |
| abstract_inverted_index.Lagrange | 150 |
| abstract_inverted_index.Thirdly, | 166 |
| abstract_inverted_index.WSR-FP+. | 190 |
| abstract_inverted_index.WSR-MM+, | 128 |
| abstract_inverted_index.Weighted | 0 |
| abstract_inverted_index.critical | 6 |
| abstract_inverted_index.efficacy | 228 |
| abstract_inverted_index.enhanced | 184 |
| abstract_inverted_index.examines | 14 |
| abstract_inverted_index.existing | 153 |
| abstract_inverted_index.gradient | 202 |
| abstract_inverted_index.proposed | 231 |
| abstract_inverted_index.repeated | 142 |
| abstract_inverted_index.sum-rate | 1 |
| abstract_inverted_index.weighted | 34 |
| abstract_inverted_index.(WSR-FP), | 45 |
| abstract_inverted_index.(WSR-MM). | 56 |
| abstract_inverted_index.Numerical | 215 |
| abstract_inverted_index.Secondly, | 122 |
| abstract_inverted_index.construed | 198 |
| abstract_inverted_index.delineate | 63 |
| abstract_inverted_index.essential | 107 |
| abstract_inverted_index.extensive | 75 |
| abstract_inverted_index.functions | 118, 135 |
| abstract_inverted_index.iteration | 162 |
| abstract_inverted_index.selecting | 133 |
| abstract_inverted_index.surrogate | 117, 134 |
| abstract_inverted_index.algorithm, | 51, 127 |
| abstract_inverted_index.coordinate | 29 |
| abstract_inverted_index.equivalent | 104, 177 |
| abstract_inverted_index.fractional | 43 |
| abstract_inverted_index.framework, | 173 |
| abstract_inverted_index.framework. | 138 |
| abstract_inverted_index.harnessing | 129 |
| abstract_inverted_index.inversions | 144 |
| abstract_inverted_index.projection | 203 |
| abstract_inverted_index.stationary | 25 |
| abstract_inverted_index.threefold. | 60 |
| abstract_inverted_index.transform, | 178 |
| abstract_inverted_index.accelerates | 164 |
| abstract_inverted_index.algorithmic | 95 |
| abstract_inverted_index.algorithms, | 32, 154 |
| abstract_inverted_index.algorithms. | 235 |
| abstract_inverted_index.comparative | 83 |
| abstract_inverted_index.connections | 219 |
| abstract_inverted_index.convergence | 23 |
| abstract_inverted_index.corroborate | 217 |
| abstract_inverted_index.demonstrate | 193 |
| abstract_inverted_index.development | 110 |
| abstract_inverted_index.flexibility | 131 |
| abstract_inverted_index.frameworks, | 96 |
| abstract_inverted_index.introducing | 174 |
| abstract_inverted_index.literature, | 79 |
| abstract_inverted_index.mean-square | 36 |
| abstract_inverted_index.multipliers | 151 |
| abstract_inverted_index.perspective | 206 |
| abstract_inverted_index.programming | 44 |
| abstract_inverted_index.simulations | 216 |
| abstract_inverted_index.sum-minimum | 35 |
| abstract_inverted_index.techniques, | 106 |
| abstract_inverted_index.theoretical | 88 |
| abstract_inverted_index.convergence. | 165 |
| abstract_inverted_index.correlations | 101 |
| abstract_inverted_index.intricacies. | 214 |
| abstract_inverted_index.maximization | 3, 41, 53 |
| abstract_inverted_index.optimization | 16 |
| abstract_inverted_index.circumventing | 140 |
| abstract_inverted_index.communication | 9 |
| abstract_inverted_index.comprehensive | 82 |
| abstract_inverted_index.computational | 159, 213 |
| abstract_inverted_index.contributions | 58 |
| abstract_inverted_index.maximization, | 20 |
| abstract_inverted_index.relationships | 66 |
| abstract_inverted_index.significantly | 156 |
| abstract_inverted_index.underpinnings | 89 |
| abstract_inverted_index.understanding | 210 |
| abstract_inverted_index.transformation | 105 |
| abstract_inverted_index.reconceptualize | 168 |
| abstract_inverted_index.minorization-maximization | 49 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |