{"id":"W3044343735","doi":"10.1109/iccworkshops49005.2020.9145398","title":"Energy-Efficient Joint Power Control and Receiver Design for Uplink mmWave-NOMA","year":2020,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Memorial University of Newfoundland","funders":"","keywords":"Telecommunications link; Beamforming; Maximization; Power control; Base station; Computer science; Optimization problem; Noma; Mathematical optimization; Power (physics); Convex optimization; Joint (building); Efficient energy use; Energy (signal processing); Electronic engineering; Regular polygon; Telecommunications; Electrical engineering; Mathematics; Engineering; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001031764,0.0001105818,0.0001381196,0.00003273971,0.00003942001,0.00002959981,0.00003851999,0.00004826448,0.00011684],"category_scores_gemma":[0.0000221033,0.00009762081,0.00004488759,0.0000426688,0.000009758861,0.00003000869,0.00001137385,0.00004857008,0.00001417638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001593381,"about_ca_system_score_gemma":0.000007465293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000183113,"about_ca_topic_score_gemma":3.347864e-7,"domain_scores_codex":[0.9994329,0.00001229462,0.0001750438,0.0001582574,0.0000628421,0.0001586146],"domain_scores_gemma":[0.9997023,0.00004446642,0.00001532072,0.00007401612,0.0000421801,0.0001217281],"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":[0.00008568975,0.00002461346,0.000005430978,0.00007657533,0.0001079921,0.000003632045,0.001052983,0.6814291,0.2910214,0.001378531,0.009234905,0.01557914],"study_design_scores_gemma":[0.0006904173,0.00006654859,0.000006091616,0.00000587772,0.00001254464,0.000001431761,0.00003732322,0.9426335,0.05437555,0.00009868509,0.001940882,0.0001311207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008927709,0.0002749109,0.9883415,0.0004709239,0.00009921709,0.0002308328,0.000004753672,0.0001993742,0.001450792],"genre_scores_gemma":[0.9747679,0.0000283638,0.02391664,0.001102973,0.00004592853,0.00001928903,0.000003015648,0.00002595969,0.00008994761],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9658402,"threshold_uncertainty_score":0.3980861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03685441431178418,"score_gpt":0.2020651195311924,"score_spread":0.1652107052194082,"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."}}