{"id":"W2145959343","doi":"10.1109/icc.2009.5198816","title":"Channel Estimation and Performance of Mismatched Decoding in Wireless Relay Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Decoding methods; Relay; Computer science; Algorithm; Channel (broadcasting); Wireless; Minimum mean square error; Bit error rate; Space–time code; Maximal-ratio combining; Real-time computing; Telecommunications; Power (physics); Statistics; Mathematics; Fading","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":[0.0002755397,0.00006185616,0.0001050668,0.00007156155,0.00006007278,0.00003310949,0.0002699027,0.00003149813,0.000002785659],"category_scores_gemma":[0.00001085931,0.00005719646,0.00001126874,0.0003277226,0.00001593633,0.0003276107,0.00008616018,0.00008747153,9.837754e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001521247,"about_ca_system_score_gemma":0.00001071745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001889963,"about_ca_topic_score_gemma":0.00001104592,"domain_scores_codex":[0.9994787,0.00004065756,0.0001833692,0.0001248916,0.00006282493,0.0001095813],"domain_scores_gemma":[0.9995815,0.00005701126,0.00005454584,0.0002405693,0.00003774065,0.0000286989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001270991,0.00005617978,0.002665153,0.00001050702,0.000003282495,9.037582e-7,0.001542798,0.03869149,0.000713174,0.05076607,0.00008030182,0.9054574],"study_design_scores_gemma":[0.0001722513,0.00005031322,0.02052342,0.00005803383,6.102318e-7,0.000002481459,0.000009234239,0.9781696,0.0008118869,0.0001310663,0.000005509766,0.00006559408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5210753,0.0001584779,0.4772909,0.000567733,0.00002790061,0.00006010073,2.109696e-8,0.00003230851,0.000787261],"genre_scores_gemma":[0.9838964,0.0009588966,0.01489533,0.0001937083,0.00000697123,0.000002509572,7.733033e-7,0.000001753975,0.00004363808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9394781,"threshold_uncertainty_score":0.2332404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02171125585595121,"score_gpt":0.2570865840515966,"score_spread":0.2353753281956454,"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."}}