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Record W2158847056 · doi:10.1109/vetecf.2002.1040340

Widely linear equalization for space-time block-coded transmission over fading ISI channels

2003· article· en· W2158847056 on OpenAlexaff
Wolfgang Gerstacker, F. Obernosterer, Robert Schober, A. Lehmann, A. Lampe, P. Gunreben

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntersymbol interferenceSpace–time block codeBlock codeFadingComputer scienceTransmit diversityTransmission (telecommunications)Equalization (audio)Time division multiple accessElectronic engineeringTelecommunicationsAlgorithmTopology (electrical circuits)Decoding methodsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

We develop receivers for transmission with space-time block codes (STBCs) over fading intersymbol interference (ISI) channels. The focus lies on Alamouti's STBC, but the results may be generalized to related codes. It turns out that a straightforward combination of conventional equalizers and a space-time block decoder is only possible if at least as many receive antennas as transmit antennas are employed, but not for the practically interesting case of pure transmit diversity. This restriction is circumvented by our approach. Equalizers with widely linear (WL) processing are designed, exploiting the structure of Alamouti's STBC, which is shown to produce an improper (rotationally variant) transmit signal. The presented receivers are especially well suited for high-level modulated signals, which are used in third-generation time-division multiple access (TDMA) mobile communications standards such as EDGE (enhanced data rates for GSM evolution). In contrast to block-based STBCs which have recently been proposed for ISI channels, our approach of combining a symbol-based STBC and equalization can be easily accommodated to channels with time-variant behaviour inside a transmission burst. Furthermore, for our scheme, the present burst structure of the EDGE system can be retained.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.780
Threshold uncertainty score0.649

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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 teacher head, not a consensus.

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

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

Citations11
Published2003
Admission routes1
Has abstractyes

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