{"id":"W2439357740","doi":"10.1049/iet-com.2016.0128","title":"Joint wavelet‐based spectrum sensing and FBMC modulation for cognitive mmWave small cell networks","year":2016,"lang":"en","type":"article","venue":"IET Communications","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Joint (building); Cognitive radio; Computer science; Modulation (music); Wavelet; Spectrum (functional analysis); Telecommunications; Artificial intelligence; Acoustics; Wireless; Physics; Engineering","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":[0.0002648732,0.0002383757,0.0001694443,0.0002687823,0.000185006,0.0002749392,0.0003027052,0.0003176932,0.0005119167],"category_scores_gemma":[0.0006096727,0.00007539193,0.0001456321,0.0002192287,0.000260345,0.0003175094,0.0002144843,0.0002391561,0.0001407994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002517296,"about_ca_system_score_gemma":0.0003293476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001156557,"about_ca_topic_score_gemma":0.00177152,"domain_scores_codex":[0.9998679,0.00002556752,0.000004896288,0.00001595831,0.00006554148,0.00002010624],"domain_scores_gemma":[0.9998616,0.00006215218,0.00001985077,0.00002064358,0.00002761063,0.000008034728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007544566,0.0002280001,0.002320938,0.0001329715,0.00005915705,0.0003595122,0.0002133559,0.1303467,0.2788532,0.03041861,0.001797842,0.5545152],"study_design_scores_gemma":[0.00001650085,0.0001594619,0.001050124,0.00001268905,0.00002069109,0.0001687744,0.00003086205,0.9396115,0.05412231,0.002771881,0.002019868,0.00001536386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1484184,0.0006887336,0.8467705,0.0002177123,0.00005975584,0.00002974548,0.00002941963,0.0001791225,0.003606636],"genre_scores_gemma":[0.9105386,0.000361523,0.08754189,0.00006382252,0.00003062063,0.00002380397,0.00002861924,0.000006083878,0.001405063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001156557,"threshold_uncertainty_score":0.002299666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04397928670828304,"score_gpt":0.2405653305535257,"score_spread":0.1965860438452427,"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."}}