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Record W4226327313 · doi:10.1109/lwc.2022.3169806

On the Achievable Capacity of Cooperative NOMA Networks: RIS or Relay?

2022· article· en· W4226327313 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

VenueIEEE Wireless Communications Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsNomaRelayComputer scienceComputer networkTelecommunicationsTelecommunications linkPower (physics)Physics

Abstract

fetched live from OpenAlex

In this letter, a novel reconfigurable intelligent surface (RIS)- and relay-assisted cooperative network with non-orthogonal multiple access (NOMA) is proposed, where the line-of-sight (LoS) and non-LoS (NLoS) scenarios are both considered for different locations of users. For the proposed cooperative NOMA systems, we first analyze the capacities of the RIS- and relay-assisted downlinks, respectively. Since it is difficult to obtain the closed-form expressions in terms of the achievable capacity, we apply the central limit theorem (CLT) and Jensen’s inequality to determine a tight upper bound for the channel gain. Then, we focus on the solutions in relay and RIS providing more capacity advantages. Numerical and simulation results verify the correctness of the derived expressions and the superiority of our proposed model. Finally, we clarify that, with different conditions of the transmit scenarios, RIS- and relay-assisted cooperative networks show their various advantages and limitations.

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 score0.110
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0040.001
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 head0.035
GPT teacher head0.241
Teacher spread0.206 · 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