Nature-Inspired Intelligent α-Fair Hybrid Precoding in Multiuser Massive Multiple-Input Multiple-Output Systems Article Swipe
Asil Koç
,
Tho Le‐Ngoc
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.36227/techrxiv.20272434
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.36227/techrxiv.20272434
This paper proposes a novel nature-inspired α-fair hybrid precoding (NI-αHP) technique for millimeter-wave multi-user massive multiple-input multiple-output systems. Unlike the existing HP literature, we propose to apply -fairness for maintaining various fairness expectations (e.g., sum-rate maximization, proportional fairness, max-min fairness, etc.). After developing the analog RF beamformer via slow time-varying angular information, the digital baseband (BB) precoder is designed via the reduced-dimensional effective channel matrix seen from the BB-stage. For the α-fairness, we derive the optimal digital BB precoder expression with a set of parameters, where optimizing them is an NP-hard problem. Hence, we efficiently optimize the parameters in the digital BB precoder via five nature-inspired intelligent algorithms. Numerical results present that when the sum-rate maximization is the target, the proposed NI-αHP technique greatly improves the sum-rate capacity and energy-efficiency performance compared to other benchmarks. Moreover, NI-αHP supports different fairness expectations and reduces the rate gap among UEs by varying the fairness level (α).
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.36227/techrxiv.20272434
- https://www.techrxiv.org/articles/preprint/Nature-Inspired_Intelligent_-Fair_Hybrid_Precoding_in_Multiuser_Massive_Multiple-Input_Multiple-Output_Systems/20272434/1/files/36210408.pdf
- OA Status
- gold
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4285042401
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4285042401Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.36227/techrxiv.20272434Digital Object Identifier
- Title
-
Nature-Inspired Intelligent α-Fair Hybrid Precoding in Multiuser Massive Multiple-Input Multiple-Output SystemsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-11Full publication date if available
- Authors
-
Asil Koç, Tho Le‐NgocList of authors in order
- Landing page
-
https://doi.org/10.36227/techrxiv.20272434Publisher landing page
- PDF URL
-
https://www.techrxiv.org/articles/preprint/Nature-Inspired_Intelligent_-Fair_Hybrid_Precoding_in_Multiuser_Massive_Multiple-Input_Multiple-Output_Systems/20272434/1/files/36210408.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.techrxiv.org/articles/preprint/Nature-Inspired_Intelligent_-Fair_Hybrid_Precoding_in_Multiuser_Massive_Multiple-Input_Multiple-Output_Systems/20272434/1/files/36210408.pdfDirect OA link when available
- Concepts
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Precoding, Maximization, Baseband, Computer science, Max-min fairness, Channel (broadcasting), Set (abstract data type), Mathematical optimization, MIMO, Bandwidth (computing), Mathematics, Telecommunications, Computer network, Resource allocation, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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37Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(α).</p> | 153 |
| abstract_inverted_index.millimeter-wave | 12 |
| abstract_inverted_index.multiple-output | 16 |
| abstract_inverted_index.nature-inspired | 5, 105 |
| abstract_inverted_index.energy-efficiency | 129 |
| abstract_inverted_index.reduced-dimensional | 61 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8999999761581421 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.05364603 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |