{"id":"W4323520982","doi":"10.1109/ieeeconf56349.2022.10052013","title":"Joint Design of User Clustering, Beamforming, and Power Allocation for NOMA","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Beamforming; Telecommunications link; Computer science; Noma; MIMO; Cluster analysis; Transmitter power output; Mathematical optimization; Quality of service; WSDMA; Resource allocation; Power (physics); Joint (building); Transmission (telecommunications); Computer network; Precoding; Engineering; Mathematics; Telecommunications; Transmitter; Artificial intelligence","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":[0.00009306405,0.00005687059,0.00008236006,0.00007067762,0.00005928614,0.000004344316,0.0001341609,0.00002185358,0.00004299279],"category_scores_gemma":[0.00002247731,0.00006063631,0.00001467088,0.0000669703,0.00002329178,0.00007708127,0.0001516354,0.0000623694,5.034565e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003925221,"about_ca_system_score_gemma":0.000004454896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002428571,"about_ca_topic_score_gemma":0.000002086004,"domain_scores_codex":[0.9996579,0.000007001357,0.0001395269,0.00006426904,0.00005112022,0.00008020015],"domain_scores_gemma":[0.9996503,0.00004562006,0.00003136317,0.000243197,0.00001955136,0.000009998006],"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":[0.00001000874,0.00001812701,0.00003789532,0.00004720813,0.00002086334,1.058072e-7,0.0003020478,0.9200184,0.05833105,0.008181878,0.0008959057,0.0121365],"study_design_scores_gemma":[0.0005928554,0.0002595465,0.000570307,0.0000128334,0.00000757433,0.000009609138,0.002025554,0.8449097,0.1207458,0.002805547,0.02777635,0.0002843048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02333939,0.0001783252,0.9754272,0.00008240536,0.00003826831,0.0002552916,0.000003911074,0.000335366,0.0003398272],"genre_scores_gemma":[0.8346403,0.00005860336,0.164959,0.0000152113,0.000001411002,0.0001807156,0.000003715951,0.00001463609,0.0001264655],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8113009,"threshold_uncertainty_score":0.2472677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0269917200701233,"score_gpt":0.2331248108767826,"score_spread":0.2061330908066593,"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."}}