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Record W2807119136 · doi:10.1109/twc.2018.2840985

Mean Delay Analysis of MIMO-ZFBF Multiplexing in Random Networks Under LOS/NLOS Path-Loss Model

2018· article· en· W2807119136 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsNon-line-of-sight propagationPath lossMIMOComputer scienceMultiplexingTelecommunicationsComputer networkWirelessBeamforming

Abstract

fetched live from OpenAlex

We analyze the performance of a multiple-input multiple-output multiplexing system in a Poisson bipolar network under line-of-sight/non-line-of-sight (LOS/NLOS) path-loss model and zero-forcing beamforming at receivers. The capacity and outage performance of such a configuration, commonly under the standard path-loss model, have been broadly analyzed; yet little is known about its local transmission delay with considering the traits of LOS/NLOS model. As the effective fading power gain on each data stream is Nakagami-type, and due to the interference correlation across data streams of a link as well as the retransmission attempts, the evaluation of the mean delay is more involved than the capacity/coverage evaluation. Our rigorous analysis provides a lower bound and an approximate upper bound on the mean delay as the functions of density, multiplexing gain, transmission activity, and LOS/NLOS model, which sheds some light on the effect of the LOS component in circumventing the possible divergence of the mean delay. Simulations show the lower bound is very accurate and demonstrate several aspects of multiplexing, path-loss traits, and interference correlation on the mean delay. Exploiting the analysis, we further explore the optimization of effective spatial throughput of the network.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.283
Teacher spread0.251 · 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