{"id":"W2085234541","doi":"10.1109/glocom.2014.7037447","title":"Closed-form Cramér-Rao lower bounds for CFO and phase estimation from turbo-coded square-QAM-modulated signals","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cramér–Rao bound; QAM; Quadrature amplitude modulation; Algorithm; Carrier frequency offset; Turbo; Computer science; Mathematics; Mean squared error; Coding gain; Turbo code; Upper and lower bounds; Estimation theory; Statistics; Decoding methods; Frequency offset; Bit error rate; Estimator; Orthogonal frequency-division multiplexing","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":[0.00453668,0.002305508,0.001124425,0.001953192,0.000601205,0.003450581,0.001507095,0.001926151,0.005770529],"category_scores_gemma":[0.03373276,0.000679543,0.0008596027,0.001551345,0.002370813,0.002980338,0.002213358,0.002628888,0.003384779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001941795,"about_ca_system_score_gemma":0.002436598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002643714,"about_ca_topic_score_gemma":0.00384504,"domain_scores_codex":[0.9971067,0.0007738785,0.0001286123,0.0003663663,0.00130262,0.0003218432],"domain_scores_gemma":[0.9858699,0.01035026,0.0007613311,0.0008696113,0.00200006,0.0001488711],"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":[0.0002163957,0.0001439997,0.001005584,0.0009739618,0.0001118931,0.0002886527,0.0004469627,0.6335437,0.0183515,0.1818401,0.007823392,0.1552538],"study_design_scores_gemma":[0.00001380842,0.00007181379,0.0004317506,0.0002207635,0.00002262373,0.0001995362,0.00009098967,0.9440683,0.01119022,0.03922988,0.004400953,0.00005950796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004163322,0.001752834,0.9865606,0.0002216854,0.00005990346,0.00005051579,0.0001698337,0.0002988066,0.00672262],"genre_scores_gemma":[0.3836755,0.006115751,0.5967788,0.0005516356,0.0004061719,0.000735959,0.001192163,0.0005536455,0.009990327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005770529,"threshold_uncertainty_score":0.02399254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668228808340895,"score_gpt":0.2917385737836369,"score_spread":0.275056285700228,"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."}}