{"id":"W4313414109","doi":"10.3390/electronics12010138","title":"Analysis of Hybrid Spectrum Sensing for 5G and 6G Waveforms","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Cognitive radio; Spectrum management; Spectrum (functional analysis); Wireless; Rician fading; Computer science; Bandwidth (computing); Radio spectrum; Quality of service; Electronic engineering; Waveform; Telecommunications; Matched filter; Frequency allocation; Filter (signal processing); Channel (broadcasting); Engineering; Physics; Fading; Radar","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":[0.0004854299,0.0003179019,0.0002577694,0.0004315665,0.0002290201,0.0004894282,0.0002731612,0.0004296629,0.00265709],"category_scores_gemma":[0.001178109,0.0001247066,0.0003946031,0.00031592,0.0002500427,0.0004388399,0.0002123038,0.0002143612,0.0002496682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003648402,"about_ca_system_score_gemma":0.0002173962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001755967,"about_ca_topic_score_gemma":0.001598053,"domain_scores_codex":[0.9996958,0.00005468521,0.000009171111,0.00004227951,0.0001647858,0.00003329842],"domain_scores_gemma":[0.99928,0.0004624758,0.00006384446,0.00003871513,0.000140225,0.00001471879],"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":[0.0009695319,0.0001363264,0.01224017,0.0002502103,0.0002502085,0.001246801,0.0003592296,0.6295742,0.1099313,0.04650627,0.001508227,0.1970275],"study_design_scores_gemma":[0.000004256488,0.00005697482,0.002753912,0.00000827899,0.00001120323,0.0001707771,0.00002473048,0.9921833,0.002884437,0.001402975,0.0004922107,0.000006942191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4949786,0.0008614777,0.4835475,0.000375059,0.0000670884,0.00007054661,0.000153395,0.0004336361,0.01951273],"genre_scores_gemma":[0.9867438,0.000109624,0.01147243,0.00002908303,0.00001352051,0.00001479262,0.00004616067,0.0000168308,0.001553776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00265709,"threshold_uncertainty_score":0.008888841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007919316433303623,"score_gpt":0.2207090146764099,"score_spread":0.2127896982431062,"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."}}