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Record W1824744182 · doi:10.1109/isssta.1998.722486

CDMA sectorized distributed antenna system

2002· article· en· W1824744182 on OpenAlexaff
Halim Yanıkömeroğlu, E.S. Sousa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDistributed antenna systemAntenna (radio)Code division multiple accessComputer scienceInterference (communication)WirelessComputer networkTelecommunicationsElectronic engineeringAntenna arrayBase stationEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

The objective of this study is to utilize antennas in novel ways so as to achieve performance benefits at the system level in future wireless networks. Despite possessing many appealing features, CDMA distributed antenna (DA) systems suffer from low capacity per antenna element (AE) as a result of the multiple access interference (MAI) accumulated in the common feeder. To overcome this capacity limitation, we propose an antenna architecture called CDMA sectorized distributed antenna (SDA). In an SDA system, a cell has many sectors in which separate feeders run, so MAI in the reverse link is reduced. In this study, the limiting case of one AE per sector is investigated. In such a case, a wireless user's signal can be picked up by all the AEs in an SDA cell, and then, can be optimally combined at a central station. It is demonstrated analytically and through simulations that in the reverse link of such a system, the SIR increases approximately linearly with an increasing number of AEs, which can be transformed into an equivalent increase in capacity and/or information rate.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.248
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2002
Admission routes1
Has abstractyes

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