{"id":"W4379619406","doi":"10.1007/s11235-023-01024-2","title":"Energy efficiency analysis and optimization for reconfigurable intelligent surface aided DF relay cooperation with minimum-rate guarantee","year":2023,"lang":"en","type":"article","venue":"Telecommunication Systems","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Relay; Computer science; Robustness (evolution); Mathematical optimization; Rayleigh fading; Transmitter power output; Optimization problem; Benchmark (surveying); Upper and lower bounds; Channel state information; Bounded function; Fractional programming; Efficient energy use; Channel (broadcasting); Power (physics); Fading; Wireless; Mathematics; Telecommunications; Algorithm; Nonlinear programming","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":[0.0005927066,0.00107786,0.0009730565,0.0003366328,0.000324649,0.001303891,0.0008939098,0.0007272346,0.003620347],"category_scores_gemma":[0.001180121,0.0003246014,0.0005259564,0.0007513411,0.0006035428,0.0008032838,0.0006616747,0.0005383914,0.0005234393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000902,"about_ca_system_score_gemma":0.0007373221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002017009,"about_ca_topic_score_gemma":0.001889402,"domain_scores_codex":[0.9996029,0.0001096074,0.00001077427,0.00005984301,0.0001126149,0.0001044118],"domain_scores_gemma":[0.9995723,0.0002432631,0.00004122921,0.00003881971,0.00009249319,0.0000118272],"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":[0.0001384912,0.0000302987,0.0002588699,0.00008672809,0.00002947641,0.00008596679,0.00004596633,0.962521,0.006986272,0.01697212,0.0008220077,0.01202271],"study_design_scores_gemma":[0.000004782538,0.00003004316,0.00007684905,0.000003681785,0.000006379762,0.00002190571,0.00001137768,0.9968414,0.0007523875,0.002076499,0.0001713128,0.000003418487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07200567,0.0009404161,0.902448,0.0004450128,0.00006989582,0.00004938884,0.0001159931,0.000205061,0.02372064],"genre_scores_gemma":[0.977638,0.0003368956,0.01812188,0.00005022255,0.00002263246,0.0000399109,0.0000458541,0.0000390983,0.003705512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003620347,"threshold_uncertainty_score":0.01211131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924647616765931,"score_gpt":0.2427838801677079,"score_spread":0.2235374040000485,"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."}}