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Record W2144003147 · doi:10.1109/icc.2001.937236

A simplified Diagonal BLAST architecture with iterative parallel-interference cancellation receivers

2002· article· en· W2144003147 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInterleavingSingle antenna interference cancellationComputer scienceDiagonalFadingDecoding methodsElectronic engineeringTurbo codeCoding (social sciences)AlgorithmEngineeringMathematics

Abstract

fetched live from OpenAlex

We propose a simplified Diagonal-BLAST (D-BLAST) architecture with parallel soft interference cancellation receiver based on the Turbo-BLAST (T-BLAST) architecture. In the T-BLAST architecture, the inter-substream coding is designed by a combination of random space-time interleaving and independent block encoding of each substream, using the same forward-error correction (FEC) code. We show that for the T-BLAST architecture, by using a systematic space-interleaving design that layers each substream diagonally across the antennas, a simplified diagonal inter-substream coding can be achieved without undue implementation complexity. The proposed diagonal inter-substream coding also facilitates the use of an iterative parallel interference cancellation receiver for decoding the simultaneously transmitted data, thereby achieving more capacity compared to the achievable capacity of traditional BLAST (Bell Labs Layered Space Time) architectures using sequential interference cancellation receivers. In this paper, we also present simulation results on fading channels, which confirm these findings.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.209
Teacher spread0.194 · 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