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Record W2600584904 · doi:10.1109/iccnc.2017.7876194

Joint RRH selection and beamforming in distributed antenna systems with energy harvesting

2017· article· en· W2600584904 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

Venue2017 International Conference on Computing, Networking and Communications (ICNC) · 2017
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceBeamformingPower budgetTransmission (telecommunications)Antenna (radio)Power (physics)Electronic engineeringWirelessMathematical optimizationTelecommunicationsElectric power systemEngineeringMathematics

Abstract

fetched live from OpenAlex

To reduce the transmission power while maintaining quality of service requirements of users, more remote radio heads (RRHs) should be active, and this in turn increases the circuit power in the distributed antenna systems with simultaneous wireless information and power transferring. Yet, the above procedures may lead to an unbalanced power consumption between transmission and circuit; therefore causes extra burden on the operators' power budget. To obtain a balanced transmission power and circuit power, this paper studies the system utility minimization problem in such a system via joint RRH selection and beamforming. The utility is formulated as the weighted sum of transmission power and circuit power. Since the formulated problem is NP-hard, a low complexity iterative algorithm is developed to achieve a near-optimal solution. The complexity of each iteration step is analyzed. Computer simulation results show the convergence of the proposed algorithm and the tradeoff between the transmission power and the circuit power.

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 score0.504
Threshold uncertainty score0.979

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.062
GPT teacher head0.267
Teacher spread0.205 · 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