{"id":"W3044698225","doi":"10.1109/lcomm.2020.3010698","title":"RFF Based Detection for SCMA in Presence of PA Nonlinearity","year":2020,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Codebook; Computer science; Robustness (evolution); Message passing; Bit error rate; Multiuser detection; Algorithm; Nonlinear system; Amplifier; Random access; Coding (social sciences); Computer engineering; Decoding methods; Code division multiple access; Bandwidth (computing); Distributed computing; Telecommunications; Computer network; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008185975,0.0004312017,0.0003940702,0.0003051799,0.0002761861,0.0004705157,0.0005482325,0.0008274406,0.0007849666],"category_scores_gemma":[0.003556921,0.0001518547,0.0002213284,0.0002786235,0.0005909751,0.0006507167,0.0005050246,0.0004878176,0.000299322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003380476,"about_ca_system_score_gemma":0.0005180686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007532247,"about_ca_topic_score_gemma":0.0009431303,"domain_scores_codex":[0.9996227,0.000147453,0.00001128834,0.00004477799,0.000140363,0.00003338457],"domain_scores_gemma":[0.9986872,0.0008637267,0.0001316738,0.0001295006,0.0001609479,0.00002689424],"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":[0.0003553547,0.00009132791,0.001891024,0.0002490039,0.00006708004,0.0004206389,0.0003015225,0.6670583,0.09196983,0.06735209,0.00131422,0.1689296],"study_design_scores_gemma":[0.000002997509,0.00003501796,0.00005529189,0.00000388966,0.000002008376,0.00005143837,0.000004488008,0.9952077,0.002999836,0.001402752,0.000230762,0.000003658977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03901524,0.0002174101,0.9583784,0.000147718,0.00003319624,0.0000280733,0.00001626517,0.0002464319,0.001917175],"genre_scores_gemma":[0.7870442,0.0002202962,0.2103017,0.00009234496,0.00003886984,0.00006728735,0.00003353769,0.00002448294,0.002177378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008274406,"threshold_uncertainty_score":0.004329205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04761774887965042,"score_gpt":0.2729470894435615,"score_spread":0.2253293405639111,"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."}}