{"id":"W4318586278","doi":"10.1109/jsac.2023.3240709","title":"Asynchronous Cell-Free Massive MIMO With Rate-Splitting","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Key Research and Development Program of China; Australian Research Council; Natural Science Foundation of Beijing Municipality; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China; ZTE Corporation","keywords":"Precoding; Asynchronous communication; Computer science; MIMO; Telecommunications link; Robustness (evolution); Channel state information; Spectral efficiency; Transmission (telecommunications); Topology (electrical circuits); Channel (broadcasting); Computer network; Telecommunications; Wireless; Mathematics","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":[0.0003359479,0.0001992462,0.0002273566,0.0004638687,0.0003152327,0.00008413054,0.0009159872,0.00009626492,0.00001357018],"category_scores_gemma":[0.0001939611,0.0001912456,0.00003766936,0.001921892,0.00004732614,0.0002611516,0.00006296395,0.0008967523,0.0000782453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00039663,"about_ca_system_score_gemma":0.0001013905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007893971,"about_ca_topic_score_gemma":0.0001383754,"domain_scores_codex":[0.9986439,0.0002167328,0.0004682733,0.0001433712,0.0001653048,0.0003623738],"domain_scores_gemma":[0.9977052,0.000545857,0.0001660159,0.001194798,0.0002797819,0.0001083175],"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":[0.00001631838,0.00005867418,0.0006568503,0.00002141825,0.00003941928,0.00002440405,0.0005240536,0.9910577,0.004417829,0.0001979682,0.002069824,0.0009155626],"study_design_scores_gemma":[0.004376653,0.0003709355,0.007789392,0.001402096,0.00007904905,0.0003011567,0.001617009,0.963303,0.01266157,0.001624633,0.005255671,0.001218809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.397242,0.002426293,0.5364671,0.003820442,0.001762614,0.002091528,0.000104057,0.004092871,0.05199315],"genre_scores_gemma":[0.9795058,0.001190322,0.01884954,0.00003698049,0.0001023947,0.00007255784,0.00004159355,0.0000857946,0.0001150197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5822638,"threshold_uncertainty_score":0.7798769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670136142362019,"score_gpt":0.2500740060430141,"score_spread":0.2333726446193939,"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."}}