{"id":"W4321769966","doi":"10.1109/lmwt.2022.3232107","title":"Load and Power Indexed Predistortion for Improved Robustness to MIMO Channel Conditions","year":2023,"lang":"en","type":"article","venue":"IEEE Microwave and Wireless Technology Letters","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Predistortion; MIMO; Precoding; Transmitter; Amplifier; Electronic engineering; Control theory (sociology); Computer science; Adjacent channel; Robustness (evolution); Linearity; Channel (broadcasting); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002368398,0.0007668154,0.0003049678,0.0003238802,0.0004890838,0.0006693489,0.0007384451,0.0006431414,0.00272304],"category_scores_gemma":[0.001203879,0.00030996,0.0002448875,0.0003088524,0.0003437138,0.001075747,0.0007128892,0.000884866,0.0009667487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003815377,"about_ca_system_score_gemma":0.0003468303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004195909,"about_ca_topic_score_gemma":0.001149502,"domain_scores_codex":[0.9996262,0.00005706669,0.00002257956,0.00009820281,0.000151464,0.00004453353],"domain_scores_gemma":[0.9994782,0.0002063849,0.00006957745,0.0001109603,0.0001185147,0.00001636133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000284026,0.0001055256,0.0009961617,0.0001965356,0.00006457433,0.0004543543,0.000304857,0.1267566,0.6323816,0.01197104,0.001627487,0.2248571],"study_design_scores_gemma":[0.00002452406,0.0002355903,0.000837651,0.00002596831,0.00005683107,0.0006637977,0.00005967005,0.6029345,0.3809541,0.002768323,0.01139171,0.00004736089],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06509199,0.0003357989,0.9257619,0.0003677953,0.0001139954,0.00004823398,0.00007505359,0.001761876,0.006443463],"genre_scores_gemma":[0.8143743,0.000274784,0.1787663,0.0002801945,0.0001347803,0.00004816327,0.0001107412,0.0001823241,0.005828343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00272304,"threshold_uncertainty_score":0.009109497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00895496478679484,"score_gpt":0.2230962237952442,"score_spread":0.2141412590084494,"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."}}