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Record W1569400750 · doi:10.1017/cbo9781107478732

Wireless Device-to-Device Communications and Networks

2015· book· en· W1569400750 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.

Bibliographic record

VenueCambridge University Press eBooks · 2015
Typebook
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceComputer networkKey (lock)Wireless networkWirelessStandardizationPhysical layerRadio resource managementWireless ad hoc networkDistributed computingTelecommunicationsComputer security

Abstract

fetched live from OpenAlex

Covering the fundamental theory together with the state-of-the-art in research and development, this practical guide provides the techniques needed to design, analyze, and optimize device-to-device (D2D) communications in wireless networking. With an ever-increasing demand for higher data rate wireless access, D2D communication is set to become a key feature supported by next generation cellular networks. This book introduces D2D-based wireless communications from the physical, MAC, network, and application layer perspectives, providing all the key background information before moving on to discuss real-world applications as well as potential future developments. Key topics are discussed in detail, such as dynamic resource sharing (for example of spectrum and power) between cellular and ad hoc D2D communications to accommodate larger volumes of traffic and provide better service to users. Readers will understand the practical challenges of resource management, optimization, security, standardization, and network topology, and learn how the design principles are applied in practice.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.215
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 science0.0010.001
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 head0.024
GPT teacher head0.213
Teacher spread0.190 · 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