{"id":"W2107084511","doi":"10.1109/tvt.2011.2157371","title":"Performance Analysis Framework for Transmit Antenna Selection Strategies of Cooperative MIMO AF Relay Networks","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Moment-generating function; MIMO; Nakagami distribution; Relay; Fading; Channel state information; Topology (electrical circuits); Cumulative distribution function; Channel (broadcasting); Mathematics; Upper and lower bounds; Signal-to-noise ratio (imaging); Maximal-ratio combining; Computer science; Algorithm; Random variable; Probability density function; Telecommunications; Statistics; Wireless; Combinatorics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000243096,0.0002131262,0.0003732368,0.0007460625,0.0004014424,0.00003728421,0.0008225103,0.0003443959,0.0000450414],"category_scores_gemma":[0.000008332378,0.0002033241,0.0002224634,0.003574646,0.0001996826,0.0003617397,0.00000606509,0.000557051,0.000004768672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004784849,"about_ca_system_score_gemma":0.00007046727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006777488,"about_ca_topic_score_gemma":0.000109399,"domain_scores_codex":[0.9986482,0.0001052873,0.0003903311,0.0004250333,0.0001295698,0.0003015236],"domain_scores_gemma":[0.9985552,0.000123141,0.000143919,0.000735743,0.0003945564,0.00004739774],"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":[0.0002225644,0.001036899,0.0006587468,0.00005601606,0.00238804,0.000005057678,0.002874341,0.5469857,0.009727125,0.2661372,0.0000285664,0.1698798],"study_design_scores_gemma":[0.0003459006,0.0006696032,0.0004739464,0.00006003135,0.0002231263,0.000009080108,0.0002170528,0.9513552,0.04534017,0.0009104075,0.0001517418,0.0002437147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04061516,0.000253475,0.9578368,0.0003130973,0.000162545,0.000349788,0.000003870091,0.0003261468,0.000139126],"genre_scores_gemma":[0.9108348,0.0009822694,0.0878865,0.00005502025,0.00001001697,0.0001734868,0.00000199769,0.00001362615,0.00004231032],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8702196,"threshold_uncertainty_score":0.8291316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02860655596243606,"score_gpt":0.2629881607961578,"score_spread":0.2343816048337218,"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."}}