MétaCan
Menu
Back to cohort
Record W1877527202 · doi:10.1109/vetecs.2004.1388929

Linear space-time transmitter and receiver processing and scheduling for the MIMO broadcast channel

2005· article· en· W1877527202 on OpenAlexaff
David Mazzarese, Witold A. Krzymień

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransmitterMIMOComputer scienceChannel (broadcasting)PrecodingThroughputScheduling (production processes)Base stationElectronic engineeringTopology (electrical circuits)Computer networkTelecommunicationsWirelessMathematicsElectrical engineeringEngineeringMathematical optimization

Abstract

fetched live from OpenAlex

We consider a MIMO broadcast channel where the transmitter and the receivers are equipped with multiple antennas. We propose a new scheme using linear processing at the transmitter and at the receivers to jointly diagonalize the channel so that two users can receive data simultaneously. It is also applicable when the users are equipped with different numbers of antennas, and it is able to take advantage of all the spatial degrees of freedom as long as the overall number of all receive antennas is greater than or equal to the number of transmit antennas. We show that the maximum throughput achievable with our scheme is larger than the maximum throughput achievable by transmitting to a single user at a time and by transmitting to several users simultaneously with receiver processing only. The proposed strategy achieves a large portion of the two-user sum-capacity when the base station has two transmit antennas. We provide an asymptotic analysis and simulation results to illustrate our analysis.

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: none
Teacher disagreement score0.782
Threshold uncertainty score0.329

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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

Citations3
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced MIMO Systems OptimizationFrench-language works237,207