{"id":"W2066075360","doi":"10.1049/cp:20030361","title":"The effect of channel estimation errors on RAKE receiver performance in WCDMA systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Rake receiver; Rake; Computer science; Interference (communication); Channel (broadcasting); Bit error rate; Multipath propagation; Electronic engineering; Noise (video); Multipath interference; Telecommunications link; Code division multiple access; Additive white Gaussian noise; Signal-to-noise ratio (imaging); Gaussian noise; Algorithm; Telecommunications; 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":[0.002152001,0.0006727342,0.0005954258,0.0005936683,0.0004000035,0.0008631574,0.0004047218,0.001273071,0.0004461684],"category_scores_gemma":[0.02819819,0.0003867082,0.0002919679,0.0007110803,0.0009874344,0.001386,0.0006112253,0.0007020523,0.0001817013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005999188,"about_ca_system_score_gemma":0.0002978057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001852372,"about_ca_topic_score_gemma":0.001270729,"domain_scores_codex":[0.9972988,0.0008637475,0.0001334581,0.0002615017,0.0009892917,0.0004532103],"domain_scores_gemma":[0.9713314,0.02360288,0.001739391,0.001333313,0.001856323,0.0001366545],"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":[0.002023304,0.00007687319,0.01765815,0.0001886698,0.0001397177,0.0005384631,0.0002484786,0.9159956,0.03187,0.001295567,0.0001639054,0.0298012],"study_design_scores_gemma":[0.00007634849,0.00180444,0.03062428,0.00008493198,0.0002347867,0.001276372,0.0001684525,0.82994,0.1337433,0.0013868,0.0005055288,0.0001548619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519538,0.0009832239,0.04527707,0.000122622,0.0000334287,0.0000149783,0.00005831108,0.000386092,0.001170423],"genre_scores_gemma":[0.9973329,0.0001402062,0.002239207,0.00001619472,0.00001191083,0.000003612677,0.0000270541,0.0000289311,0.0001999786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002152001,"threshold_uncertainty_score":0.01138097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733633043155782,"score_gpt":0.2724001329279364,"score_spread":0.2550638024963786,"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."}}