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Record W2136593844 · doi:10.1109/vetecf.2007.116

PIC Assisted IBDFE Based Iterative Spatial Channel Estimation with Intra and Inter-Cell Interference in SC-FDE System

2007· article· en· W2136593844 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Vehicular Technology Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTelecommunications linkSingle antenna interference cancellationInterference (communication)Computer scienceEqualization (audio)Channel (broadcasting)Orthogonal frequency-division multiplexingElectronic engineeringAlgorithmIterative methodTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

In this paper, the issue of channel estimation in Single Carrier Frequency Domain Equalization (SC-FDE) uplink Space Division Multiple Access (SDMA) systems in the presence of intra and inter-cell interference is addressed. It is shown that in such an interference-prone system, a combination of orthogonal pilots, spatial processing and Iterative Channel Estimation (ICE) is effective. Adaptive Iterative Block Soft Decision based Feedback Equalizer (IBDFE) with Parallel Interference Cancellation (PIC) assisted Decision Feedback Iterative Channel Estimation is employed. It is shown that such a combination is a promising way to suppress uplink inter-user interference.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.679
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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