{"id":"W4386973824","doi":"10.1109/lwc.2023.3318432","title":"Performance of OTFS-NOMA Scheme for Coordinated Direct and Relay Transmission Networks in High-Mobility Scenarios","year":2023,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer science; Noma; Relay; Transmission (telecommunications); Topology (electrical circuits); Outage probability; Interference (communication); Transformation (genetics); Electronic engineering; Algorithm; Computer network; Decoding methods; Mathematics; Telecommunications; Telecommunications link; Engineering; Fading; Power (physics); Channel (broadcasting); Physics","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":[0.001488212,0.0009195704,0.0007139682,0.0005258684,0.0007473098,0.001010453,0.0005775977,0.0007198122,0.0009747396],"category_scores_gemma":[0.003675712,0.0001706248,0.000367345,0.0006559579,0.000913475,0.0007942913,0.001026299,0.0004191026,0.0001770055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000869189,"about_ca_system_score_gemma":0.001066623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002736049,"about_ca_topic_score_gemma":0.003994249,"domain_scores_codex":[0.9989353,0.0004359151,0.00004106187,0.0001104318,0.0002409192,0.0002363597],"domain_scores_gemma":[0.9980185,0.001056561,0.0002278757,0.0002638249,0.0003436358,0.00008967131],"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":[0.001165779,0.0001462107,0.005950605,0.0002747347,0.0001559374,0.0009349157,0.0004160081,0.8449568,0.03472418,0.02649823,0.002004526,0.08277211],"study_design_scores_gemma":[0.00002662834,0.000343402,0.001377035,0.00001762601,0.00004273473,0.0004092437,0.0001478978,0.9881364,0.005602608,0.003342798,0.0005212411,0.00003227144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6150032,0.001934774,0.3665704,0.000520721,0.0001629176,0.00008976636,0.0002021485,0.0005741273,0.0149421],"genre_scores_gemma":[0.9917452,0.0001650109,0.007677045,0.00003200303,0.00001072022,0.00001612461,0.00002649926,0.000005084685,0.0003222592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002736049,"threshold_uncertainty_score":0.007870495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01634016714081739,"score_gpt":0.2399928815101284,"score_spread":0.223652714369311,"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."}}