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Record W2098699135 · doi:10.5539/nct.v1n2p28

Open Wireless System Cloud: An Architecture for Future Wireless Communications System

2012· article· en· W2098699135 on OpenAlexvenueno aff
Jianwen Chen, Xiang Chen, Jing Liu, Ming Zhao

Bibliographic record

VenueNetwork and Communication Technologies · 2012
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsMunicipal wireless networkWirelessComputer networkComputer scienceWi-Fi arrayCognitive radioWireless intrusion prevention systemWireless networkWireless WANRadio resource managementCloud computingFixed wirelessFlexibility (engineering)Telecommunications

Abstract

fetched live from OpenAlex

Open Wireless System Cloud (OWSC) is a radio access network architecture for future wireless communication systems with remote radio heads, centralized wireless computation on open platforms, and cooperative wireless signal processing and management. With centralized wireless signal processing, system capacity can be increased using emerging wireless techniques, such as cognitive radio, or collaborative processing and coordinated multipoint transmission (CoMP). Centralized open computing platform provides greater flexibility as the system can simultaneously support multi-standards and services, such as 2G, 3G and 4G as well as multiple type wireless applications. With this open architecture, OWSC can serve as infrastructure for researchers and wireless resource provider and can be supplied by 3rd parties much like Amazon provides AWS today. The barrier to entry for new entrant wireless operator role is greatly reduced. This enables new business models for the future mobile networks and service providers.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.008
Open science0.0040.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.004

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 head0.041
GPT teacher head0.293
Teacher spread0.252 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations5
Published2012
Admission routes1
Has abstractyes

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