{"id":"W3124815611","doi":"10.1109/tcomm.2021.3053613","title":"Achievable Rate Characterization of NOMA-Aided Cell-Free Massive MIMO With Imperfect Successive Interference Cancellation","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Telecommunications link; Computer science; MIMO; Noma; Power control; Single antenna interference cancellation; Path loss; Transmitter power output; Channel state information; Moment (physics); Context (archaeology); Control theory (sociology); Topology (electrical circuits); Computer network; Channel (broadcasting); Mathematics; Telecommunications; Power (physics); Wireless; Transmitter","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008677617,0.0002302967,0.0002811816,0.0002177432,0.0003027172,0.00004150247,0.001189824,0.000131212,0.00007269027],"category_scores_gemma":[0.00002256388,0.0002429779,0.00007528615,0.0008361439,0.0002276921,0.0004085893,0.00002607205,0.0005268195,0.00001779042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001622556,"about_ca_system_score_gemma":0.0001025911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002789684,"about_ca_topic_score_gemma":0.0004208587,"domain_scores_codex":[0.9988402,0.0001627008,0.0004285877,0.0002216579,0.000138096,0.0002087541],"domain_scores_gemma":[0.9956378,0.0004338312,0.0001919856,0.003324729,0.0003603514,0.00005124275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000402498,0.0002465251,0.00003682254,0.00008924924,0.000107144,0.000001597057,0.0005903866,0.2101195,0.7789276,0.0006289395,0.0000298858,0.009182048],"study_design_scores_gemma":[0.000631513,0.00008341419,0.0003493095,0.0001672748,0.00005180833,0.000004292033,0.0004728792,0.04887271,0.9484417,0.0002379476,0.0004030258,0.000284065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09104057,0.0003380374,0.9045593,0.0008848225,0.00013223,0.0003253154,0.0001762364,0.0005543313,0.001989197],"genre_scores_gemma":[0.9854894,0.00374795,0.0100347,0.00002658516,0.000005903071,0.0002469609,0.0001188126,0.00005147886,0.0002782067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8945246,"threshold_uncertainty_score":0.990835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460945588071688,"score_gpt":0.2290979670656028,"score_spread":0.214488511184886,"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."}}