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Record W1488783168 · doi:10.5772/6821

Joint MIMO Channel Tracking and Symbol Decoding

2009· book-chapter· en· W1488783168 on OpenAlexaff
Balasubramanian Balakumar, T. Kirubaraj

Bibliographic record

VenueInTech eBooks · 2009
Typebook-chapter
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDecoding methodsJoint (building)Symbol (formal)Channel (broadcasting)Computer scienceMIMOTracking (education)TelecommunicationsPsychologyEngineering

Abstract

fetched live from OpenAlex

In this Chapter, an efficient Kalman filtering solution for the problem of channel tracking in MIMO communication systems where the MIMO channel is time-varying is presented. Considering the type of MIMO systems where orthogonal space-time block codes are used to encode the information symbols a two-step MIMO channel tracking algorithm is presented. As the first step, Kalman filtering is used to obtain an initial channel estimate for the current block based on the channel estimates obtained for previous blocks. In the second step, the so-obtained initial channel estimate is refined using a decision-directed iterative

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.914
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
Bibliometrics0.0000.000
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 head0.035
GPT teacher head0.250
Teacher spread0.215 · 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.

Study designOther design
Domainnot available
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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