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Record W2962849865 · doi:10.1109/itw.2018.8613531

Capacity Limits of Full-Duplex Cellular Network

2018· article· en· W2962849865 on OpenAlex
Kaiming Shen, Reza K. Farsani, Wei Yu

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTelecommunications linkBase stationComputer scienceCellular networkComputer networkRelayBottleneckDuplex (building)Interference (communication)ConverseTransmitterChannel (broadcasting)MathematicsPhysicsEmbedded system

Abstract

fetched live from OpenAlex

This paper explores the information theoretical capacity limits of uplink-downlink transmissions in a wireless cellular network with full-duplex FD base station (BS) and half-duplex user terminals. We recognize the cross-channel interference between the terminals as the main capacity bottleneck, and propose novel strategies that use BS as a relay to facilitate interference cancellation. We model the FD cellular system as a two-user interference channel with an extra cross-link feedback from the uplink receiver to the downlink transmitter, and show that the feedback allows a larger achievable rate region than the conventional non-feedback schemes. This paper further provides a converse and shows that the proposed scheme achieves the capacity of the full-duplex cellular network to within a constant additive gap. Finally, this paper considers a new scenario in which the uplink terminal has additional information to transmit to the downlink terminal directly. Relaying by the BS is shown to play a crucial role in maximizing the achievable rates in this case.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.699

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)0.0010.000

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 head0.030
GPT teacher head0.221
Teacher spread0.191 · 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

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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