{"id":"W2071971234","doi":"10.1109/vetecf.2010.5594502","title":"On the Performance of Imperfect Channel Estimation for Vehicular Ad-Hoc Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Rayleigh fading; Channel (broadcasting); Bit error rate; Wireless ad hoc network; Transmit diversity; Antenna diversity; Imperfect; Transmission (telecommunications); Vehicular ad hoc network; Fading; Orthogonal frequency-division multiplexing; Space–time block code; Computer network; Telecommunications; Wireless","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":[0.003406278,0.001005012,0.0009202593,0.0005119882,0.0006241207,0.0009938565,0.0006551788,0.0009676749,0.0005017737],"category_scores_gemma":[0.02801368,0.0004375602,0.000235672,0.00068594,0.001772294,0.001607503,0.00117736,0.0008018777,0.0001426017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001474409,"about_ca_system_score_gemma":0.001118723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007152937,"about_ca_topic_score_gemma":0.004842444,"domain_scores_codex":[0.9979086,0.000859578,0.00006332865,0.0001533165,0.0006315627,0.0003836958],"domain_scores_gemma":[0.9780701,0.01814015,0.001330914,0.0008206752,0.001474305,0.0001638188],"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":[0.00009117972,0.00001072477,0.0009427023,0.00003004661,0.00001842453,0.0000634655,0.00003660247,0.9906562,0.0009482064,0.003423519,0.0001243879,0.003654555],"study_design_scores_gemma":[0.000008022118,0.00007917531,0.001086768,0.00001632786,0.00002177811,0.00007725143,0.00003667528,0.9928813,0.002144179,0.003492508,0.0001365864,0.00001943992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.567255,0.002587488,0.4198548,0.0008224869,0.0001103108,0.00006221977,0.0002585148,0.0003972638,0.008651927],"genre_scores_gemma":[0.9955759,0.000434199,0.003509008,0.00002815084,0.00001690692,0.0000118993,0.00004618224,0.00001498566,0.0003627564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007152937,"threshold_uncertainty_score":0.01801431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195748200837962,"score_gpt":0.2603753848397753,"score_spread":0.2384179028313957,"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."}}