{"id":"W2990012747","doi":"10.1109/tvt.2019.2956167","title":"UAV-Assisted Cooperative Communications With Time-Sharing Information and Power Transfer","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Relay; Maximum power transfer theorem; Computer science; Wireless; Throughput; Transmission (telecommunications); Convergence (economics); Maximization; Optimization problem; Mathematical optimization; Information transfer; Power (physics); Trajectory; Transmitter power output; Computer network; Algorithm; Channel (broadcasting); Telecommunications; Mathematics; Transmitter","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":[0.0003093454,0.0005893425,0.000562367,0.0002178271,0.0003260498,0.0004926905,0.0006814695,0.000565036,0.0005496633],"category_scores_gemma":[0.000695479,0.0001994467,0.0003132253,0.0005319917,0.0003618776,0.000797194,0.0007375656,0.0003738783,0.000171336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002902032,"about_ca_system_score_gemma":0.0004045399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656103,"about_ca_topic_score_gemma":0.001531871,"domain_scores_codex":[0.9996835,0.0000978208,0.00001566967,0.00007434686,0.00008069852,0.00004805113],"domain_scores_gemma":[0.9996836,0.0001412611,0.00006353793,0.00004235979,0.00005484148,0.00001442421],"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":[0.0002056988,0.00007216701,0.0008790492,0.0001316182,0.00008149994,0.0003300822,0.0002412345,0.8769307,0.03020525,0.01692125,0.0008478445,0.07315367],"study_design_scores_gemma":[0.0000100312,0.00008500016,0.0001295894,0.000003513093,0.00001355168,0.00007646,0.00003303195,0.9925338,0.003561226,0.002702775,0.0008440322,0.00000684711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06266571,0.0004295203,0.9329768,0.00009448605,0.00003637547,0.00002801234,0.00002823748,0.0001210995,0.003619772],"genre_scores_gemma":[0.9463776,0.000228114,0.05091623,0.00003877959,0.000016826,0.0000463838,0.00003202893,0.000009774784,0.002334223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001656103,"threshold_uncertainty_score":0.003292978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005418697857696483,"score_gpt":0.1876936377131606,"score_spread":0.1822749398554642,"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."}}