{"id":"W2958475640","doi":"10.1109/twc.2020.2991995","title":"Overlap-Save FBMC Receivers","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Filter bank; Quadrature amplitude modulation; Asynchronous communication; MIMO; Electronic engineering; Spectral efficiency; Bit error rate; Algorithm; Telecommunications; Decoding methods; Beamforming; Engineering; Channel (broadcasting)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005320414,0.0001916148,0.0001855532,0.0001184286,0.0003365281,0.00004105362,0.0007788484,0.0001080267,0.0002091768],"category_scores_gemma":[0.000005116932,0.0002323643,0.0001315939,0.0005599492,0.000153496,0.0002189098,0.000003924376,0.000613198,0.0006617444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001338828,"about_ca_system_score_gemma":0.00003169302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001755887,"about_ca_topic_score_gemma":0.00002827827,"domain_scores_codex":[0.9990528,0.00007264882,0.0002845793,0.0001900503,0.0001796968,0.0002202159],"domain_scores_gemma":[0.9983557,0.0001545105,0.00003626168,0.001202811,0.00005844844,0.0001922815],"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":[0.00006297437,0.0004490587,0.00005817363,0.0001307546,0.0005437238,0.000004676983,0.005302343,0.8141069,0.05600206,0.003726738,0.0131559,0.1064567],"study_design_scores_gemma":[0.001903966,0.0002113315,0.0003182671,0.0001581981,0.0002376342,0.00003736614,0.002580562,0.6575542,0.1242201,0.0002641708,0.2109639,0.0015503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0403164,0.0004130564,0.9113727,0.01049072,0.001539412,0.0006237268,0.0002457889,0.003306513,0.03169172],"genre_scores_gemma":[0.9948198,0.001437485,0.003014778,0.0002976921,0.00004721561,0.0001189518,0.00001207188,0.00005975186,0.0001922169],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9545034,"threshold_uncertainty_score":0.9475542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03752547898097042,"score_gpt":0.2523092699930196,"score_spread":0.2147837910120491,"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."}}