{"id":"W2071879168","doi":"10.1155/2008/580368","title":"Performance of Multiple-Relay Cooperative Diversity Systems with Best Relay Selection over Rayleigh Fading Channels","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Relay; Rayleigh fading; Cooperative diversity; Relay channel; Node (physics); Computer science; Fading; Computer network; Signal-to-noise ratio (imaging); Interference (communication); Diversity gain; Diversity combining; Telecommunications; Topology (electrical circuits); Channel (broadcasting); Mathematics; Power (physics); Engineering; Physics","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":[0.001772133,0.001474789,0.001414573,0.0006155045,0.000771887,0.001493654,0.0007980357,0.001298505,0.0009584411],"category_scores_gemma":[0.004721189,0.0003973953,0.0005108441,0.0006728997,0.001581039,0.001209469,0.001370187,0.0005639981,0.0002192066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001298259,"about_ca_system_score_gemma":0.001067774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007421467,"about_ca_topic_score_gemma":0.003060562,"domain_scores_codex":[0.9987332,0.0005043584,0.00004759055,0.0001606627,0.0002292391,0.0003249709],"domain_scores_gemma":[0.9949805,0.003195224,0.0004971738,0.0002459108,0.0008859152,0.0001952589],"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":[0.0003337528,0.00003024936,0.001820729,0.00006404119,0.00007259531,0.0002050874,0.0001006658,0.9865632,0.004097959,0.002890506,0.0001992057,0.003621934],"study_design_scores_gemma":[0.000027154,0.0001967519,0.0007862029,0.000009235026,0.00003792761,0.00007940727,0.00005447509,0.9955309,0.001301243,0.001873189,0.00007847144,0.00002507825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8573071,0.00191722,0.130488,0.0004680757,0.00006722967,0.00004721198,0.000257698,0.0003686189,0.009078771],"genre_scores_gemma":[0.9982734,0.0001637116,0.001214996,0.00001652427,0.0000100177,0.000007778567,0.00002621444,0.000006300279,0.0002811247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007421467,"threshold_uncertainty_score":0.01475656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0358092712235222,"score_gpt":0.274050797603345,"score_spread":0.2382415263798228,"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."}}