Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks Article Swipe
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2203.00714
We consider a cell-free wireless system operated in Time Division Duplex (TDD) mode with user-centric clusters of remote radio units (RUs). Since the uplink pilot dimensions per channel coherence slot is limited, co-pilot users might incur mutual pilot contamination. In the current literature, it is assumed that the long-term statistical knowledge of all user channels is available. This enables Minimum Mean-Square Error channel estimation or simplified dominant subspace projection, which achieves significant pilot decontamination under certain assumptions on the channel covariance matrices. However, estimating the channel covariance matrix or even just its dominant subspace at all RUs forming a user cluster is not an easy task. In fact, if not properly designed, a piloting scheme for such long-term statistics estimation will also be subject to the contamination problem. In this paper, we propose a new channel subspace estimation scheme explicitly designed for cell-free wireless networks. Our scheme is based on 1) a sounding reference signal (SRS) using latin squares wideband frequency hopping, and 2) a subspace estimation method based on robust Principal Component Analysis (R-PCA). The SRS hopping scheme ensures that for any user and any RU participating in its cluster, only a few pilot measurements will contain strong co-pilot interference. These few heavily contaminated measurements are (implicitly) eliminated by R-PCA, which is designed to regularize the estimation and discount the ``outlier'' measurements. Our simulation results show that the proposed scheme achieves almost perfect subspace knowledge, which in turns yields system performance very close to that with ideal channel state information, thus essentially solving the problem of pilot contamination in cell-free user-centric TDD wireless networks.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2203.00714
- https://arxiv.org/pdf/2203.00714
- OA Status
- green
- Cited By
- 4
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4226542773
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4226542773Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2203.00714Digital Object Identifier
- Title
-
Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless NetworksWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-01Full publication date if available
- Authors
-
Fabian Göttsch, Noboru Osawa, Takeo Ohseki, Kosuke Yamazaki, Giuseppe CaireList of authors in order
- Landing page
-
https://arxiv.org/abs/2203.00714Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2203.00714Direct 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/2203.00714Direct OA link when available
- Concepts
-
Subspace topology, Computer science, Telecommunications link, Signal subspace, Covariance matrix, Channel (broadcasting), Outlier, Algorithm, Covariance, Channel state information, Wireless, Real-time computing, Statistics, Computer network, Mathematics, Telecommunications, Noise (video), Artificial intelligence, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4226542773 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2203.00714 |
| ids.doi | https://doi.org/10.48550/arxiv.2203.00714 |
| ids.openalex | https://openalex.org/W4226542773 |
| fwci | |
| type | preprint |
| title | Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12791 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.995199978351593 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2208 |
| topics[0].subfield.display_name | Electrical and Electronic Engineering |
| topics[0].display_name | Full-Duplex Wireless Communications |
| topics[1].id | https://openalex.org/T10931 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9646999835968018 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1711 |
| topics[1].subfield.display_name | Signal Processing |
| topics[1].display_name | Direction-of-Arrival Estimation Techniques |
| topics[2].id | https://openalex.org/T10860 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9613999724388123 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1711 |
| topics[2].subfield.display_name | Signal Processing |
| topics[2].display_name | Speech and Audio Processing |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C32834561 |
| concepts[0].level | 2 |
| concepts[0].score | 0.662287712097168 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q660730 |
| concepts[0].display_name | Subspace topology |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6399797797203064 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C138660444 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5940789580345154 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q5607897 |
| concepts[2].display_name | Telecommunications link |
| concepts[3].id | https://openalex.org/C2777121530 |
| concepts[3].level | 4 |
| concepts[3].score | 0.580058217048645 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q7512739 |
| concepts[3].display_name | Signal subspace |
| concepts[4].id | https://openalex.org/C185142706 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5717670321464539 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1134404 |
| concepts[4].display_name | Covariance matrix |
| concepts[5].id | https://openalex.org/C127162648 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5578624606132507 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q16858953 |
| concepts[5].display_name | Channel (broadcasting) |
| concepts[6].id | https://openalex.org/C79337645 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5297160148620605 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q779824 |
| concepts[6].display_name | Outlier |
| concepts[7].id | https://openalex.org/C11413529 |
| concepts[7].level | 1 |
| concepts[7].score | 0.4838503897190094 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[7].display_name | Algorithm |
| concepts[8].id | https://openalex.org/C178650346 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4555980861186981 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q201984 |
| concepts[8].display_name | Covariance |
| concepts[9].id | https://openalex.org/C148063708 |
| concepts[9].level | 3 |
| concepts[9].score | 0.4319302439689636 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q5072511 |
| concepts[9].display_name | Channel state information |
| concepts[10].id | https://openalex.org/C555944384 |
| concepts[10].level | 2 |
| concepts[10].score | 0.38456156849861145 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q249 |
| concepts[10].display_name | Wireless |
| concepts[11].id | https://openalex.org/C79403827 |
| concepts[11].level | 1 |
| concepts[11].score | 0.33858075737953186 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q3988 |
| concepts[11].display_name | Real-time computing |
| concepts[12].id | https://openalex.org/C105795698 |
| concepts[12].level | 1 |
| concepts[12].score | 0.24977895617485046 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[12].display_name | Statistics |
| concepts[13].id | https://openalex.org/C31258907 |
| concepts[13].level | 1 |
| concepts[13].score | 0.21683573722839355 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[13].display_name | Computer network |
| concepts[14].id | https://openalex.org/C33923547 |
| concepts[14].level | 0 |
| concepts[14].score | 0.2108837068080902 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[14].display_name | Mathematics |
| concepts[15].id | https://openalex.org/C76155785 |
| concepts[15].level | 1 |
| concepts[15].score | 0.1836332082748413 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[15].display_name | Telecommunications |
| concepts[16].id | https://openalex.org/C99498987 |
| concepts[16].level | 3 |
| concepts[16].score | 0.1674235463142395 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q2210247 |
| concepts[16].display_name | Noise (video) |
| concepts[17].id | https://openalex.org/C154945302 |
| concepts[17].level | 1 |
| concepts[17].score | 0.13913550972938538 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[17].display_name | Artificial intelligence |
| concepts[18].id | https://openalex.org/C115961682 |
| concepts[18].level | 2 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[18].display_name | Image (mathematics) |
| keywords[0].id | https://openalex.org/keywords/subspace-topology |
| keywords[0].score | 0.662287712097168 |
| keywords[0].display_name | Subspace topology |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6399797797203064 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/telecommunications-link |
| keywords[2].score | 0.5940789580345154 |
| keywords[2].display_name | Telecommunications link |
| keywords[3].id | https://openalex.org/keywords/signal-subspace |
| keywords[3].score | 0.580058217048645 |
| keywords[3].display_name | Signal subspace |
| keywords[4].id | https://openalex.org/keywords/covariance-matrix |
| keywords[4].score | 0.5717670321464539 |
| keywords[4].display_name | Covariance matrix |
| keywords[5].id | https://openalex.org/keywords/channel |
| keywords[5].score | 0.5578624606132507 |
| keywords[5].display_name | Channel (broadcasting) |
| keywords[6].id | https://openalex.org/keywords/outlier |
| keywords[6].score | 0.5297160148620605 |
| keywords[6].display_name | Outlier |
| keywords[7].id | https://openalex.org/keywords/algorithm |
| keywords[7].score | 0.4838503897190094 |
| keywords[7].display_name | Algorithm |
| keywords[8].id | https://openalex.org/keywords/covariance |
| keywords[8].score | 0.4555980861186981 |
| keywords[8].display_name | Covariance |
| keywords[9].id | https://openalex.org/keywords/channel-state-information |
| keywords[9].score | 0.4319302439689636 |
| keywords[9].display_name | Channel state information |
| keywords[10].id | https://openalex.org/keywords/wireless |
| keywords[10].score | 0.38456156849861145 |
| keywords[10].display_name | Wireless |
| keywords[11].id | https://openalex.org/keywords/real-time-computing |
| keywords[11].score | 0.33858075737953186 |
| keywords[11].display_name | Real-time computing |
| keywords[12].id | https://openalex.org/keywords/statistics |
| keywords[12].score | 0.24977895617485046 |
| keywords[12].display_name | Statistics |
| keywords[13].id | https://openalex.org/keywords/computer-network |
| keywords[13].score | 0.21683573722839355 |
| keywords[13].display_name | Computer network |
| keywords[14].id | https://openalex.org/keywords/mathematics |
| keywords[14].score | 0.2108837068080902 |
| keywords[14].display_name | Mathematics |
| keywords[15].id | https://openalex.org/keywords/telecommunications |
| keywords[15].score | 0.1836332082748413 |
| keywords[15].display_name | Telecommunications |
| keywords[16].id | https://openalex.org/keywords/noise |
| keywords[16].score | 0.1674235463142395 |
| keywords[16].display_name | Noise (video) |
| keywords[17].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[17].score | 0.13913550972938538 |
| keywords[17].display_name | Artificial intelligence |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2203.00714 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2203.00714 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2203.00714 |
| locations[1].id | doi:10.48550/arxiv.2203.00714 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2203.00714 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5031847523 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7897-177X |
| authorships[0].author.display_name | Fabian Göttsch |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Göttsch, Fabian |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5061381969 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Noboru Osawa |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Osawa, Noboru |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5045093210 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3993-5893 |
| authorships[2].author.display_name | Takeo Ohseki |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Ohseki, Takeo |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5073000411 |
| authorships[3].author.orcid | https://orcid.org/0009-0003-5747-9024 |
| authorships[3].author.display_name | Kosuke Yamazaki |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Yamazaki, Kosuke |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5058252389 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-7749-1333 |
| authorships[4].author.display_name | Giuseppe Caire |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Caire, Giuseppe |
| authorships[4].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2203.00714 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T12791 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.995199978351593 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2208 |
| primary_topic.subfield.display_name | Electrical and Electronic Engineering |
| primary_topic.display_name | Full-Duplex Wireless Communications |
| related_works | https://openalex.org/W4313028534, https://openalex.org/W4328007667, https://openalex.org/W2789380668, https://openalex.org/W2170465046, https://openalex.org/W2108247409, https://openalex.org/W3022667867, https://openalex.org/W2047534115, https://openalex.org/W2348690876, https://openalex.org/W2138981061, https://openalex.org/W4285309764 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2203.00714 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2203.00714 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2203.00714 |
| primary_location.id | pmh:oai:arXiv.org:2203.00714 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2203.00714 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2203.00714 |
| publication_date | 2022-03-01 |
| publication_year | 2022 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 2, 98, 112, 133, 151, 164, 192 |
| abstract_inverted_index.1) | 150 |
| abstract_inverted_index.2) | 163 |
| abstract_inverted_index.In | 39, 106, 128 |
| abstract_inverted_index.RU | 186 |
| abstract_inverted_index.We | 0 |
| abstract_inverted_index.an | 103 |
| abstract_inverted_index.at | 94 |
| abstract_inverted_index.be | 122 |
| abstract_inverted_index.by | 209 |
| abstract_inverted_index.if | 108 |
| abstract_inverted_index.in | 7, 188, 237, 259 |
| abstract_inverted_index.is | 30, 44, 55, 101, 147, 212 |
| abstract_inverted_index.it | 43 |
| abstract_inverted_index.of | 16, 51, 256 |
| abstract_inverted_index.on | 77, 149, 169 |
| abstract_inverted_index.or | 64, 88 |
| abstract_inverted_index.to | 124, 214, 244 |
| abstract_inverted_index.we | 131 |
| abstract_inverted_index.Our | 145, 223 |
| abstract_inverted_index.RUs | 96 |
| abstract_inverted_index.SRS | 176 |
| abstract_inverted_index.TDD | 262 |
| abstract_inverted_index.The | 175 |
| abstract_inverted_index.all | 52, 95 |
| abstract_inverted_index.and | 162, 184, 218 |
| abstract_inverted_index.any | 182, 185 |
| abstract_inverted_index.are | 206 |
| abstract_inverted_index.few | 193, 202 |
| abstract_inverted_index.for | 115, 141, 181 |
| abstract_inverted_index.its | 91, 189 |
| abstract_inverted_index.new | 134 |
| abstract_inverted_index.not | 102, 109 |
| abstract_inverted_index.per | 26 |
| abstract_inverted_index.the | 22, 40, 47, 78, 84, 125, 216, 220, 228, 254 |
| abstract_inverted_index.This | 57 |
| abstract_inverted_index.Time | 8 |
| abstract_inverted_index.also | 121 |
| abstract_inverted_index.easy | 104 |
| abstract_inverted_index.even | 89 |
| abstract_inverted_index.just | 90 |
| abstract_inverted_index.mode | 12 |
| abstract_inverted_index.only | 191 |
| abstract_inverted_index.show | 226 |
| abstract_inverted_index.slot | 29 |
| abstract_inverted_index.such | 116 |
| abstract_inverted_index.that | 46, 180, 227, 245 |
| abstract_inverted_index.this | 129 |
| abstract_inverted_index.thus | 251 |
| abstract_inverted_index.user | 53, 99, 183 |
| abstract_inverted_index.very | 242 |
| abstract_inverted_index.will | 120, 196 |
| abstract_inverted_index.with | 13, 246 |
| abstract_inverted_index.(SRS) | 155 |
| abstract_inverted_index.(TDD) | 11 |
| abstract_inverted_index.Error | 61 |
| abstract_inverted_index.Since | 21 |
| abstract_inverted_index.These | 201 |
| abstract_inverted_index.based | 148, 168 |
| abstract_inverted_index.close | 243 |
| abstract_inverted_index.fact, | 107 |
| abstract_inverted_index.ideal | 247 |
| abstract_inverted_index.incur | 35 |
| abstract_inverted_index.latin | 157 |
| abstract_inverted_index.might | 34 |
| abstract_inverted_index.pilot | 24, 37, 72, 194, 257 |
| abstract_inverted_index.radio | 18 |
| abstract_inverted_index.state | 249 |
| abstract_inverted_index.task. | 105 |
| abstract_inverted_index.turns | 238 |
| abstract_inverted_index.under | 74 |
| abstract_inverted_index.units | 19 |
| abstract_inverted_index.users | 33 |
| abstract_inverted_index.using | 156 |
| abstract_inverted_index.which | 69, 211, 236 |
| abstract_inverted_index.(RUs). | 20 |
| abstract_inverted_index.Duplex | 10 |
| abstract_inverted_index.R-PCA, | 210 |
| abstract_inverted_index.almost | 232 |
| abstract_inverted_index.matrix | 87 |
| abstract_inverted_index.method | 167 |
| abstract_inverted_index.mutual | 36 |
| abstract_inverted_index.paper, | 130 |
| abstract_inverted_index.remote | 17 |
| abstract_inverted_index.robust | 170 |
| abstract_inverted_index.scheme | 114, 138, 146, 178, 230 |
| abstract_inverted_index.signal | 154 |
| abstract_inverted_index.strong | 198 |
| abstract_inverted_index.system | 5, 240 |
| abstract_inverted_index.uplink | 23 |
| abstract_inverted_index.yields | 239 |
| abstract_inverted_index.Minimum | 59 |
| abstract_inverted_index.assumed | 45 |
| abstract_inverted_index.certain | 75 |
| abstract_inverted_index.channel | 27, 62, 79, 85, 135, 248 |
| abstract_inverted_index.cluster | 100 |
| abstract_inverted_index.contain | 197 |
| abstract_inverted_index.current | 41 |
| abstract_inverted_index.enables | 58 |
| abstract_inverted_index.ensures | 179 |
| abstract_inverted_index.forming | 97 |
| abstract_inverted_index.heavily | 203 |
| abstract_inverted_index.hopping | 177 |
| abstract_inverted_index.perfect | 233 |
| abstract_inverted_index.problem | 255 |
| abstract_inverted_index.propose | 132 |
| abstract_inverted_index.results | 225 |
| abstract_inverted_index.solving | 253 |
| abstract_inverted_index.squares | 158 |
| abstract_inverted_index.subject | 123 |
| abstract_inverted_index.(R-PCA). | 174 |
| abstract_inverted_index.Analysis | 173 |
| abstract_inverted_index.Division | 9 |
| abstract_inverted_index.However, | 82 |
| abstract_inverted_index.achieves | 70, 231 |
| abstract_inverted_index.channels | 54 |
| abstract_inverted_index.cluster, | 190 |
| abstract_inverted_index.clusters | 15 |
| abstract_inverted_index.co-pilot | 32, 199 |
| abstract_inverted_index.consider | 1 |
| abstract_inverted_index.designed | 140, 213 |
| abstract_inverted_index.discount | 219 |
| abstract_inverted_index.dominant | 66, 92 |
| abstract_inverted_index.hopping, | 161 |
| abstract_inverted_index.limited, | 31 |
| abstract_inverted_index.operated | 6 |
| abstract_inverted_index.piloting | 113 |
| abstract_inverted_index.problem. | 127 |
| abstract_inverted_index.properly | 110 |
| abstract_inverted_index.proposed | 229 |
| abstract_inverted_index.sounding | 152 |
| abstract_inverted_index.subspace | 67, 93, 136, 165, 234 |
| abstract_inverted_index.wideband | 159 |
| abstract_inverted_index.wireless | 4, 143, 263 |
| abstract_inverted_index.Component | 172 |
| abstract_inverted_index.Principal | 171 |
| abstract_inverted_index.cell-free | 3, 142, 260 |
| abstract_inverted_index.coherence | 28 |
| abstract_inverted_index.designed, | 111 |
| abstract_inverted_index.frequency | 160 |
| abstract_inverted_index.knowledge | 50 |
| abstract_inverted_index.long-term | 48, 117 |
| abstract_inverted_index.matrices. | 81 |
| abstract_inverted_index.networks. | 144, 264 |
| abstract_inverted_index.reference | 153 |
| abstract_inverted_index.available. | 56 |
| abstract_inverted_index.covariance | 80, 86 |
| abstract_inverted_index.dimensions | 25 |
| abstract_inverted_index.eliminated | 208 |
| abstract_inverted_index.estimating | 83 |
| abstract_inverted_index.estimation | 63, 119, 137, 166, 217 |
| abstract_inverted_index.explicitly | 139 |
| abstract_inverted_index.knowledge, | 235 |
| abstract_inverted_index.regularize | 215 |
| abstract_inverted_index.simplified | 65 |
| abstract_inverted_index.simulation | 224 |
| abstract_inverted_index.statistics | 118 |
| abstract_inverted_index.Mean-Square | 60 |
| abstract_inverted_index.``outlier'' | 221 |
| abstract_inverted_index.assumptions | 76 |
| abstract_inverted_index.essentially | 252 |
| abstract_inverted_index.literature, | 42 |
| abstract_inverted_index.performance | 241 |
| abstract_inverted_index.projection, | 68 |
| abstract_inverted_index.significant | 71 |
| abstract_inverted_index.statistical | 49 |
| abstract_inverted_index.(implicitly) | 207 |
| abstract_inverted_index.contaminated | 204 |
| abstract_inverted_index.information, | 250 |
| abstract_inverted_index.measurements | 195, 205 |
| abstract_inverted_index.user-centric | 14, 261 |
| abstract_inverted_index.contamination | 126, 258 |
| abstract_inverted_index.interference. | 200 |
| abstract_inverted_index.measurements. | 222 |
| abstract_inverted_index.participating | 187 |
| abstract_inverted_index.contamination. | 38 |
| abstract_inverted_index.decontamination | 73 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |