{"id":"W3037616208","doi":"10.1109/twc.2020.3003615","title":"Multi-Antenna Two-Way Relay Based Cooperative NOMA","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; Southeast University; National Natural Science Foundation of China","keywords":"Computer science; Noma; Relay; Transmission (telecommunications); Antenna (radio); Cooperative diversity; Benchmark (surveying); Diversity gain; Reliability (semiconductor); Selection (genetic algorithm); Antenna diversity; Computer network; Wireless; Telecommunications; Power (physics); MIMO; Wireless network; Beamforming; Telecommunications link; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008364864,0.001168375,0.001015502,0.0004604064,0.0006045955,0.001056482,0.00139888,0.001043107,0.0009570104],"category_scores_gemma":[0.001368194,0.000321193,0.0007182094,0.000827809,0.0006892466,0.001143784,0.001071475,0.0004627855,0.0004010427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005342397,"about_ca_system_score_gemma":0.0004881965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001171159,"about_ca_topic_score_gemma":0.001553691,"domain_scores_codex":[0.9990225,0.0005007847,0.0000377229,0.0001431656,0.000168699,0.0001270854],"domain_scores_gemma":[0.9989562,0.0005414507,0.0001405134,0.0001296066,0.0001859209,0.00004625727],"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":[0.0002943336,0.0001841759,0.001661903,0.0003986026,0.0002784996,0.001610979,0.0003855189,0.8860275,0.03089516,0.04384737,0.001399345,0.03301667],"study_design_scores_gemma":[0.00001680328,0.0001549663,0.000132513,0.000006979845,0.00003409124,0.0003127471,0.00004238195,0.9938492,0.002019944,0.00268729,0.0007272944,0.00001579748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1229768,0.001982957,0.8617383,0.0003159821,0.0001151613,0.0001329292,0.0001250547,0.000294421,0.01231848],"genre_scores_gemma":[0.9559529,0.0005288547,0.04061417,0.00008443819,0.00003047115,0.00009015768,0.00003536674,0.00001060745,0.002653117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00139888,"threshold_uncertainty_score":0.004423857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04588430924726003,"score_gpt":0.2771615728414337,"score_spread":0.2312772635941736,"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."}}