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Record W1513597564 · doi:10.1109/vtc.2002.1002700

A new software radio based distributed base station architecture and its application to 3G UMTS employing signal combining techniques

2003· article· en· W1513597564 on OpenAlexaff
Hong Nie, P. Takis Mathiopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsUMTS frequency bandsBase stationCDMA2000Computer scienceSoftware-defined radioSoftwareEmbedded systemGSMSIGNAL (programming language)Real-time computingComputer hardwareComputer networkCode division multiple accessTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

We propose a software radio based distributed base station (DBS) architecture which replaces conventional base stations with a cluster of DBS and a central processing station (CPS) which are connected by a high speed data communication network. As most signal processing is carried out in the CPS, the DBS is compact and lightweight, and requires low power for operation, so it can be deployed economically and virtually everywhere. Furthermore, since the radio signals received by different DBS are processed in one CPS, signal combining techniques (SCT) can be employed to improve the reverse link capacity of the 3G UMTS. Analytical expressions for this improvement are derived using the concept of percentage of coverage area with and without the SCT. Complementary computer simulation results for a cdma2000 system have also shown that by employing the SCT, the proposed software radio based DBS architecture can achieve significant reverse link capacity improvement.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.283
Teacher spread0.262 · 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

Citations2
Published2003
Admission routes1
Has abstractyes

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