{"id":"W1990784032","doi":"10.1109/icc.2014.6883682","title":"Energy-efficient resource allocation in full-duplex relaying networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Science Foundation","keywords":"Stackelberg competition; Computer science; Efficient energy use; Resource allocation; Game theory; Subgame perfect equilibrium; Subgame; Mathematical optimization; Transmitter power output; Spectral efficiency; Iterative method; Telecommunications link; Bandwidth (computing); Computer network; Nash equilibrium; Transmitter; Best response; Algorithm; Mathematics; Engineering; Mathematical economics","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":[0.001062877,0.0004910331,0.0006655136,0.0003824855,0.0003928911,0.001088855,0.0008676032,0.000785538,0.0009767648],"category_scores_gemma":[0.00193827,0.0003796745,0.0003221821,0.000532634,0.0008792253,0.00120998,0.0007849969,0.0003236089,0.0001423987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009141729,"about_ca_system_score_gemma":0.000828805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002049914,"about_ca_topic_score_gemma":0.002047729,"domain_scores_codex":[0.9992174,0.0003589408,0.00002985962,0.00009789621,0.0001556303,0.0001401642],"domain_scores_gemma":[0.9990514,0.0006834405,0.0001003581,0.00004344544,0.00007758863,0.00004373502],"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":[0.0001415312,0.00005478723,0.0004896059,0.00008043162,0.00003834162,0.0003009941,0.0001541176,0.8989637,0.009406522,0.06724857,0.0004457324,0.02267559],"study_design_scores_gemma":[0.00001312155,0.00005113006,0.0001518602,0.000004181119,0.000008113268,0.00006127017,0.00003090625,0.9779329,0.001265382,0.02006895,0.0004006176,0.00001145949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1350091,0.0004931281,0.8577027,0.0001702596,0.00001939905,0.0000668284,0.00006097389,0.00009202735,0.006385513],"genre_scores_gemma":[0.972689,0.0002163149,0.02538788,0.00002738816,0.00000876327,0.00005131608,0.00001693208,0.000007998079,0.001594412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002049914,"threshold_uncertainty_score":0.006632805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008488105818481076,"score_gpt":0.1959846379284608,"score_spread":0.1874965321099797,"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."}}