{"id":"W3100612237","doi":"","title":"1Resource Allocation Under Channel Uncertainties for Relay-Aided Device-to-Device Communication Underlaying LTE-A Cellular Networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Relay; Computer science; Robustness (evolution); Cellular network; Computer network; Resource allocation; Quality of service; Spectral efficiency; Optimization problem; Mathematical optimization; Channel (broadcasting); Power (physics); Mathematics; Algorithm","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":[0.001010877,0.0007273483,0.0007916726,0.0003311085,0.0004761622,0.000960944,0.000476619,0.0007315201,0.0009798789],"category_scores_gemma":[0.003172629,0.0002748074,0.0003328127,0.0004612518,0.0007142516,0.0007918928,0.0009040427,0.0006041745,0.00009350012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411726,"about_ca_system_score_gemma":0.0008339332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008106431,"about_ca_topic_score_gemma":0.004437572,"domain_scores_codex":[0.9995047,0.0002177137,0.00001539899,0.00006856371,0.00009183557,0.0001017751],"domain_scores_gemma":[0.9985044,0.00105512,0.0001782556,0.00004936406,0.00017033,0.00004255488],"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":[0.0000344137,0.00000643001,0.0001817217,0.00001563253,0.000007521244,0.00004122924,0.000009009713,0.9957634,0.0006765187,0.001286448,0.00009839595,0.001879226],"study_design_scores_gemma":[0.000002075884,0.00001320958,0.00007672544,0.000001371741,0.000002453187,0.000006357096,0.000006416947,0.9991704,0.0002451943,0.0004389292,0.00003436912,0.000002520644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2224339,0.000831979,0.770313,0.0004091211,0.00005043478,0.00006455174,0.0001484328,0.0002005551,0.005548149],"genre_scores_gemma":[0.9927657,0.000101195,0.006692749,0.00001856488,0.00000712819,0.00001640222,0.00002435421,0.000006452662,0.0003674473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008106431,"threshold_uncertainty_score":0.01611853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02432287597738753,"score_gpt":0.2416604782319757,"score_spread":0.2173376022545882,"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."}}