{"id":"W2577665255","doi":"10.1109/lcomm.2017.2655052","title":"Antenna Selection in MIMO Cognitive AF Relay Networks With Mutual Interference and Limited Feedback","year":2017,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Lakehead University","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Semiconductor Research Corporation","keywords":"Cognitive radio; Computer science; Rayleigh fading; Relay; MIMO; Interference (communication); Diversity gain; Antenna (radio); Selection (genetic algorithm); Mutual information; Transmitter; Fading; Electronic engineering; Telecommunications; Topology (electrical circuits); Control theory (sociology); Power (physics); Mathematics; Wireless; Channel (broadcasting); Engineering; Machine learning; Artificial intelligence","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":[0.0001594526,0.0002026781,0.0002037347,0.0001770767,0.00056768,0.000195447,0.001297169,0.00009686142,0.000005989451],"category_scores_gemma":[0.00007838091,0.0002152262,0.00002921333,0.0002406884,0.0005404736,0.0004369262,0.0002557735,0.000761663,0.00001976718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001047291,"about_ca_system_score_gemma":0.00001612578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001913582,"about_ca_topic_score_gemma":0.003398679,"domain_scores_codex":[0.9990409,0.0001338573,0.0002730379,0.0001984535,0.00008544572,0.0002683182],"domain_scores_gemma":[0.9975534,0.0003985036,0.0001142168,0.001775829,0.00008869907,0.00006931798],"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":[0.0004091367,0.0007393505,0.1948812,0.0001863857,0.0009253022,0.0000275483,0.01305539,0.6039558,0.1442731,0.001231461,0.005609327,0.03470594],"study_design_scores_gemma":[0.0008484427,0.00004186719,0.1189895,0.000448983,0.00003764411,0.00002778835,0.0003079801,0.8782903,0.0003405506,0.000002743642,0.0003187497,0.0003454718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758385,0.0005087971,0.01878604,0.003562,0.00008189106,0.0003229014,0.00001083345,0.0002241147,0.0006649679],"genre_scores_gemma":[0.993554,0.001307457,0.004592519,0.0002509796,0.00002674332,0.000154751,0.00003690736,0.00004645805,0.00003017435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2743345,"threshold_uncertainty_score":0.8776671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02612295938986229,"score_gpt":0.2484030690522123,"score_spread":0.22228010966235,"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."}}