{"id":"W2905589904","doi":"10.1109/twc.2018.2886903","title":"Downlink MU-MIMO With QoS Aware Transmission: Precoder Design and Performance Analysis","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada)","funders":"","keywords":"Computer science; Telecommunications link; Multicast; Precoding; Unicast; Base station; MIMO; Minimum mean square error; Algorithm; Computer network; Transmission (telecommunications); Channel (broadcasting); Mathematics; Estimator; Telecommunications; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009788643,0.001495006,0.0008253055,0.0003799548,0.0005448607,0.001131192,0.0006684507,0.001128988,0.002110105],"category_scores_gemma":[0.003142909,0.0004911188,0.0003863521,0.0007871239,0.000610409,0.0007903113,0.0007663362,0.0009707226,0.0007344542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000775173,"about_ca_system_score_gemma":0.001370773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003506885,"about_ca_topic_score_gemma":0.004366522,"domain_scores_codex":[0.9990535,0.0003231739,0.00002893834,0.0001090242,0.0003522998,0.0001330586],"domain_scores_gemma":[0.9986517,0.0006922176,0.0001142429,0.0001120046,0.0003908954,0.00003899163],"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":[0.0002702015,0.0001101335,0.00143766,0.0004153464,0.0001230704,0.0003487855,0.0001891437,0.8149617,0.02744126,0.04214624,0.00251994,0.1100366],"study_design_scores_gemma":[0.0000168454,0.0001689243,0.0003664388,0.00003104563,0.00003394511,0.0002627873,0.0000344313,0.9879313,0.005906141,0.003664282,0.001563474,0.00002049929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0123602,0.001341444,0.9795306,0.0002495483,0.00006583038,0.00007526854,0.0001072736,0.0002496226,0.006020272],"genre_scores_gemma":[0.7725758,0.003986661,0.2168388,0.0003893666,0.0003396464,0.0002931482,0.0003351435,0.00006417515,0.005177164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003506885,"threshold_uncertainty_score":0.007058978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02487771192018315,"score_gpt":0.251609052161276,"score_spread":0.2267313402410929,"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."}}