{"id":"W2162153797","doi":"10.1109/cnsr.2008.86","title":"Improved Compensation of HPA Nonlinearities Using Digital Predistorters with Dynamic and Multi-dimensional LUTs","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Predistortion; Orthogonal frequency-division multiplexing; Lookup table; Nonlinear distortion; Electronic engineering; Computer science; Adjacent channel; Amplifier; Multipath propagation; Dynamic range; Adjacent-channel interference; Spectral efficiency; Control theory (sociology); Channel (broadcasting); Interference (communication); Telecommunications; Engineering; Bandwidth (computing)","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":[0.00001459183,0.0001025435,0.0001221107,0.00004729583,0.00003439924,0.000008321576,0.00002538506,0.00002977598,0.000005673022],"category_scores_gemma":[0.000004189009,0.00009236378,0.00001420517,0.00004767698,0.00009960594,0.0002542723,0.00001253837,0.00005492095,5.709566e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000429151,"about_ca_system_score_gemma":0.00001592082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001333756,"about_ca_topic_score_gemma":0.0000128717,"domain_scores_codex":[0.9995632,0.00000317687,0.0001339602,0.0001038756,0.00008543694,0.0001103701],"domain_scores_gemma":[0.9997827,0.00002897465,0.00002376257,0.00008874452,0.00003704338,0.00003871989],"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":[0.0002498463,0.0002273167,0.01632831,0.0003928567,0.0003322572,0.0000688177,0.002900512,0.5308565,0.4432455,0.0001228963,0.0001006732,0.005174548],"study_design_scores_gemma":[0.0005240561,0.00004023146,0.005188552,0.00001983903,0.000007422782,0.00009318406,0.00006315707,0.9919342,0.001975222,0.000008981502,0.00001279524,0.0001323977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.614732,0.00005432049,0.3848698,0.00000175922,0.00004573669,0.00008899709,0.00002099696,0.00008171282,0.00010475],"genre_scores_gemma":[0.8866966,0.000003390045,0.1131484,0.00000535195,0.000007020284,0.00000161611,0.00001766447,0.000020118,0.00009984514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4610777,"threshold_uncertainty_score":0.3766485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578250730776346,"score_gpt":0.2121297114003431,"score_spread":0.1963472040925797,"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."}}