Analyzing Uplink SINR and Rate in Massive MIMO Systems Using Stochastic Geometry Article Swipe
Tianyang Bai
,
Robert W. Heath
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1510.02538
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1510.02538
This paper proposes a stochastic geometry framework to analyze the SINR and rate performance in a large-scale uplink massive MIMO network. Based on the model, expressions are derived for spatial average SINR distributions over user and base station distributions with maximum ratio combining (MRC) and zero-forcing (ZF) receivers. We show that using massive MIMO, the uplink SINR in certain urban marco-cell scenarios is limited by interference. In the interference-limited regime, the results reveal that for MRC receivers, a super-linear (polynomial) scaling law between the number of base station antennas and scheduled users per cell preserves the uplink SIR distribution, while a linear scaling applies to ZF receivers. ZF receivers are shown to outperform MRC receivers in the SIR coverage, and the performance gap is quantified in terms of the difference in the number of antennas to achieve the same SIR distribution. Numerical results verify the analysis. It is found that the optimal compensation fraction in fractional power control to optimize rate is generally different for MRC and ZF receivers. Besides, simulations show that the scaling results derived from the proposed framework apply to the networks where base stations are distributed according to a hexagonal lattice.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1510.02538
- https://arxiv.org/pdf/1510.02538
- OA Status
- green
- Cited By
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1910232789
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W1910232789Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1510.02538Digital Object Identifier
- Title
-
Analyzing Uplink SINR and Rate in Massive MIMO Systems Using Stochastic GeometryWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-10-09Full publication date if available
- Authors
-
Tianyang Bai, Robert W. HeathList of authors in order
- Landing page
-
https://arxiv.org/abs/1510.02538Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1510.02538Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1510.02538Direct OA link when available
- Concepts
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Stochastic geometry, Telecommunications link, Base station, MIMO, Topology (electrical circuits), Scaling, Computer science, Mathematics, Coverage probability, Algorithm, Geometry, Statistics, Computer network, Combinatorics, Beamforming, Confidence intervalTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2020: 1, 2018: 1, 2017: 1, 2016: 3Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.regime, | 69 |
| abstract_inverted_index.results | 71, 142, 175 |
| abstract_inverted_index.scaling | 80, 102, 174 |
| abstract_inverted_index.spatial | 29 |
| abstract_inverted_index.station | 37, 87 |
| abstract_inverted_index.Besides, | 169 |
| abstract_inverted_index.antennas | 88, 134 |
| abstract_inverted_index.fraction | 153 |
| abstract_inverted_index.geometry | 5 |
| abstract_inverted_index.lattice. | 194 |
| abstract_inverted_index.network. | 20 |
| abstract_inverted_index.networks | 184 |
| abstract_inverted_index.optimize | 159 |
| abstract_inverted_index.proposed | 179 |
| abstract_inverted_index.proposes | 2 |
| abstract_inverted_index.stations | 187 |
| abstract_inverted_index.Numerical | 141 |
| abstract_inverted_index.according | 190 |
| abstract_inverted_index.analysis. | 145 |
| abstract_inverted_index.combining | 42 |
| abstract_inverted_index.coverage, | 118 |
| abstract_inverted_index.different | 163 |
| abstract_inverted_index.framework | 6, 180 |
| abstract_inverted_index.generally | 162 |
| abstract_inverted_index.hexagonal | 193 |
| abstract_inverted_index.preserves | 94 |
| abstract_inverted_index.receivers | 108, 114 |
| abstract_inverted_index.scenarios | 61 |
| abstract_inverted_index.scheduled | 90 |
| abstract_inverted_index.difference | 129 |
| abstract_inverted_index.fractional | 155 |
| abstract_inverted_index.marco-cell | 60 |
| abstract_inverted_index.outperform | 112 |
| abstract_inverted_index.quantified | 124 |
| abstract_inverted_index.receivers, | 76 |
| abstract_inverted_index.receivers. | 47, 106, 168 |
| abstract_inverted_index.stochastic | 4 |
| abstract_inverted_index.distributed | 189 |
| abstract_inverted_index.expressions | 25 |
| abstract_inverted_index.large-scale | 16 |
| abstract_inverted_index.performance | 13, 121 |
| abstract_inverted_index.simulations | 170 |
| abstract_inverted_index.(polynomial) | 79 |
| abstract_inverted_index.compensation | 152 |
| abstract_inverted_index.super-linear | 78 |
| abstract_inverted_index.zero-forcing | 45 |
| abstract_inverted_index.distribution, | 98 |
| abstract_inverted_index.distribution. | 140 |
| abstract_inverted_index.distributions | 32, 38 |
| abstract_inverted_index.interference. | 65 |
| abstract_inverted_index.interference-limited | 68 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.800000011920929 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile |