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Record W2126455699 · doi:10.1109/pimrc.2001.965389

Technology comparisons in wireless local loop

2002· article· en· W2126455699 on OpenAlexaff
Haiying Zhu, Luc Boucher, M. Wachira

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsLocal loopWireless broadbandBroadbandTelecommunicationsComputer scienceNarrowbandDigital Enhanced Cordless TelecommunicationsWirelessBroadband networksBase transceiver stationEmerging technologiesWireless networkDigital subscriber lineWi-Fi array

Abstract

fetched live from OpenAlex

Economic factors and emerging technologies are the two main forces that are making WLL solutions a reality. WLL uses wireless technology coupled with line interfaces and other circuitry to complete the "last mile" between the customer's premises and the PSTN. In this survey paper, current WLL technologies are introduced. WLL is broadly categorized into two classes: narrowband and broadband. The fact that WLL is competing with other fixed access technologies is emphasized and the comparison with other competing technologies is shown. Capacity and functionality of different technologies employed in WLL systems are briefly compared. DECT, PACS, and PHS are compared in greater detail through quantitative evaluations. In the broadband area, the planning for terrestrial and satellite-based broadband networks used to supply WLL in urban environments is compared.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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 designNot applicable
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

Citations1
Published2002
Admission routes1
Has abstractyes

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