{"id":"W3027314774","doi":"10.1109/lcomm.2020.3029178","title":"Power Allocation and Link Selection for Multicell Cooperative NOMA Hybrid VLC/RF Systems","year":2020,"lang":"en","type":"preprint","venue":"IEEE Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; King Fahd University of Petroleum and Minerals; King Abdullah University of Science and Technology","keywords":"Visible light communication; Computer science; Noma; Computer network; Transmitter power output; Context (archaeology); Interference (communication); Quality of service; Throughput; Power (physics); Telecommunications; Transmitter; Wireless; Telecommunications link; Engineering; Electrical engineering; Physics; Channel (broadcasting)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006831501,0.0007142376,0.000567393,0.0003410443,0.0004466037,0.0007868183,0.0007224087,0.0005847109,0.000848027],"category_scores_gemma":[0.001351037,0.0003278383,0.0002518266,0.000583968,0.0006086251,0.0005932952,0.0006515094,0.0004252726,0.0002367693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006365794,"about_ca_system_score_gemma":0.0006415616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002536067,"about_ca_topic_score_gemma":0.004597631,"domain_scores_codex":[0.9994326,0.0002528726,0.00001165129,0.00007157704,0.0001480981,0.00008315095],"domain_scores_gemma":[0.9995012,0.0003203129,0.000071352,0.00002728677,0.00005975999,0.00001999902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006949745,0.00006386884,0.0005851184,0.00005320673,0.00003001717,0.00008411518,0.00007449229,0.9431512,0.005797735,0.007809075,0.0005426523,0.04173899],"study_design_scores_gemma":[0.000008751077,0.00003429166,0.0000935986,0.000002662364,0.000004678971,0.00001921199,0.0000143363,0.9967114,0.0005925478,0.002177208,0.0003375839,0.000003799618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0539849,0.0006570604,0.9409547,0.0001639757,0.00003333927,0.00003929176,0.00002505134,0.0001284873,0.004013346],"genre_scores_gemma":[0.9262276,0.0002913399,0.07075083,0.00007258916,0.00004971435,0.00007121232,0.00002470249,0.0000294806,0.002482585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002536067,"threshold_uncertainty_score":0.005042613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0337323102557506,"score_gpt":0.2705100149551514,"score_spread":0.2367777046994008,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}