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Record W2020813517 · doi:10.1049/ip-com:20040969

MIMO OFDM for broadband fixed wireless access

2005· article· en· W2020813517 on OpenAlexaff
T.J. Willink

Bibliographic record

VenueIEE Proceedings - Communications · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsMIMOOrthogonal frequency-division multiplexingMultipath propagationSpatial multiplexingSpatial correlationChannel (broadcasting)Antenna diversityComputer scienceSpectral efficiencyMIMO-OFDMElectronic engineeringDelay spreadWirelessDiversity schemeDiversity gainBroadbandMultiplexingTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

A broadband multiple-input multiple-output (MIMO) OFDM system has been designed and evaluated for a fixed wireless link between tall buildings in an urban area. Channel measurements for a typical installation location are analysed to determine the relevant spatial, temporal and frequency characteristics. The small number of multipath components leads to a high spatial correlation and limited potential for spatial diversity to provide spectral efficiency gains. However, the slowly-varying characteristics support the use of a closed-loop diversity scheme, such as spatial multiplexing along the eigenmodes of the channel matrix, to maximise the achievable throughput. This scheme is evaluated using the measured channel data, and it is shown that the self-interference caused by channel estimation errors is the limiting factor on the system performance. Taking into account the estimation errors and feedback delay, it is demonstrated that a three-fold increase in spectral efficiency relative to a single-element antenna system is achievable using eight-element antennas, even in this highly correlated environment.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

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)0.0030.001

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 head0.042
GPT teacher head0.322
Teacher spread0.280 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations19
Published2005
Admission routes1
Has abstractyes

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