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Record W1549494129 · doi:10.1109/pimrc.2003.1259120

Frequency domain equalization for MIMO space-time transmissions with single carrier signaling

2004· article· en· W1549494129 on OpenAlexaff
Z. Zhang, J. How

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMIMOOrthogonal frequency-division multiplexingIntersymbol interferenceElectronic engineeringComputer scienceFadingContext (archaeology)MIMO-OFDMEqualization (audio)Channel (broadcasting)Topology (electrical circuits)TelecommunicationsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

This paper presents a space-time multiple-input and multiple-output (MIMO) transceiver for reliable transmissions over frequency selective fading channels using conventional single-carrier M-ary PSK or QAM modulations. The novelty of the proposed scheme is in efficient exploiting the induced circulant structure of the new signaling in the context of MIMO setup so that the intersymbol interference (ISI) effects could be fully mitigated at the receiver using algebraic solutions. It is demonstrated through Monte-Carlo simulations that the performance of this scheme over time-dispersive channels is comparable to that of MIMO-OFDM. OFDM has high peak to average power ratio (PAPR) and demands the use of highly linear power amplifiers (PA). The proposed scheme offers the advantage of reduced constraints on the PA linearity, which is critical in wireless applications.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.001

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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations0
Published2004
Admission routes1
Has abstractyes

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