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Record W2786027207 · doi:10.1049/pbte074e_ch13

Spectral coexistence for next generation wireless backhaul networks

2017· book-chapter· en· W2786027207 on OpenAlex
Shree Krishna Sharma, Eva Lagunas, Christos G. Tsinos, Sina Maleki, Symeon Chatzinotas, Björn Ottersten

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

VenueInstitution of Engineering and Technology eBooks · 2017
Typebook-chapter
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsBackhaul (telecommunications)Computer scienceWirelessTelecommunicationsWireless networkComputer networkRadio spectrumDistributed computing

Abstract

fetched live from OpenAlex

In this chapter, starting with the recent trend in terrestrial and satellite backhaul technologies, we provide possible use cases for HSTB networks and their potential benefits and challenges. Subsequently, we focus on the spectrum sharing aspects of wireless backhaul networks considering the following two categories of enabling techniques: (i) spectral awareness techniques and (ii) spectral exploitation techniques. The first category mainly comprises radio environment awareness techniques such as spectrum sensing and databases while the second category includes interference mitigation and resource allocation techniques. Furthermore, we present three case studies along with the numerical results considering the coexistence of satellite and terrestrial systems in the Ka-band. Finally, this chapter provides some interesting recommendations for future research directions.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
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 science0.0000.000
Research integrity0.0010.000
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 head0.049
GPT teacher head0.234
Teacher spread0.185 · 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