Analysis of Linear Precoding Techniques for Massive MIMO-OFDM Systems under various scenarios Article Swipe
D Subitha
,
R. Váni
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1757-899x/1084/1/012053
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1757-899x/1084/1/012053
Emerging 5G technology is largely supported by the base station signal processing techniques such as precoding. Precoding combines the input signals in a predefined way and deliver them in a right proportion to the multiple antenna elements. Such precoding algorithms are crucial for the design of the emerging 5G technology; massive MIMO system. In this paper, the performance of various linear precoding algorithms such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Conjugate Gradient (CG) based precoding are analyzed in terms of Bit Error Rate (BER) and achievable sum-rate. The results are analyzed under various channel conditions such as rural, sub urban and urban. The above algorithms are tested for MIMO-OFDM system. OFDM system simulated here uses 52 subcarriers and a Base Station equipped with more than 100 antennas serving multiple users simultaneously. The channel models are stochastic channels simulated using WINNER II modeling.
Related Topics
Concepts
Precoding
Zero-forcing precoding
Orthogonal frequency-division multiplexing
Computer science
MIMO
Base station
MIMO-OFDM
Conjugate gradient method
Bit error rate
Electronic engineering
Channel (broadcasting)
Algorithm
Telecommunications
Engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1757-899x/1084/1/012053
- OA Status
- diamond
- Cited By
- 12
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3134281818
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3134281818Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1757-899x/1084/1/012053Digital Object Identifier
- Title
-
Analysis of Linear Precoding Techniques for Massive MIMO-OFDM Systems under various scenariosWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-03-01Full publication date if available
- Authors
-
D Subitha, R. VániList of authors in order
- Landing page
-
https://doi.org/10.1088/1757-899x/1084/1/012053Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
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https://doi.org/10.1088/1757-899x/1084/1/012053Direct OA link when available
- Concepts
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Precoding, Zero-forcing precoding, Orthogonal frequency-division multiplexing, Computer science, MIMO, Base station, MIMO-OFDM, Conjugate gradient method, Bit error rate, Electronic engineering, Channel (broadcasting), Algorithm, Telecommunications, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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12Total citation count in OpenAlex
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2024: 1, 2023: 4, 2022: 4, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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9Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.various | 60, 97 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Emerging | 1 |
| abstract_inverted_index.Gradient | 76 |
| abstract_inverted_index.analyzed | 81, 95 |
| abstract_inverted_index.antennas | 131 |
| abstract_inverted_index.channels | 141 |
| abstract_inverted_index.combines | 18 |
| abstract_inverted_index.emerging | 48 |
| abstract_inverted_index.equipped | 126 |
| abstract_inverted_index.multiple | 35, 133 |
| abstract_inverted_index.Conjugate | 75 |
| abstract_inverted_index.MIMO-OFDM | 113 |
| abstract_inverted_index.Precoding | 17 |
| abstract_inverted_index.elements. | 37 |
| abstract_inverted_index.modeling. | 146 |
| abstract_inverted_index.precoding | 39, 62, 79 |
| abstract_inverted_index.simulated | 117, 142 |
| abstract_inverted_index.sum-rate. | 91 |
| abstract_inverted_index.supported | 6 |
| abstract_inverted_index.achievable | 90 |
| abstract_inverted_index.algorithms | 40, 63, 109 |
| abstract_inverted_index.conditions | 99 |
| abstract_inverted_index.precoding. | 16 |
| abstract_inverted_index.predefined | 24 |
| abstract_inverted_index.processing | 12 |
| abstract_inverted_index.proportion | 32 |
| abstract_inverted_index.stochastic | 140 |
| abstract_inverted_index.techniques | 13 |
| abstract_inverted_index.technology | 3 |
| abstract_inverted_index.performance | 58 |
| abstract_inverted_index.subcarriers | 121 |
| abstract_inverted_index.technology; | 50 |
| abstract_inverted_index.simultaneously. | 135 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5078360155, https://openalex.org/A5072068788 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I1330855593, https://openalex.org/I145286018 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.8500000238418579 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.97286139 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |