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TUCKER2-based Hybrid Beamforming Design for mmWave OFDM Massive MIMO Communications

2021· article· en· W3166072085 on OpenAlexafffund
Guilherme Martignago Zilli, Wei‐Ping Zhu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBasebandSubcarrierComputer scienceOrthogonal frequency-division multiplexingMIMOElectronic engineeringBeamformingSingular value decompositionPrecodingMIMO-OFDMInterference (communication)Computational complexity theoryOrthogonalityChannel (broadcasting)AlgorithmTelecommunicationsBandwidth (computing)MathematicsEngineering

Abstract

fetched live from OpenAlex

This paper proposes a novel joint hybrid precoder and combiner design for maximizing the average achievable sum-rate of single-user OFDM millimeter wave massive MIMO systems. The analog precoder and combiner design is formulated as a constrained Tucker2 decomposition and solved using the projected alternate least square method. This formulation allows maximizing the sum of the effective baseband gains over every subcarrier while suppressing the interference among the same subcarrier’s data streams. The digital precoder and combiner are obtained from the effective baseband channel’s singular value decomposition on a per-subcarrier basis. Numerical simulation results show that the proposed method outperforms some of the existing designs while having similar computational complexity.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.233
Threshold uncertainty score0.590

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 head0.033
GPT teacher head0.257
Teacher spread0.223 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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