{"id":"W2524190195","doi":"10.1109/jsyst.2015.2464238","title":"Spectral–Energy Efficiency Tradeoff in Full-Duplex Two-Way Relay Networks","year":2015,"lang":"en","type":"article","venue":"IEEE Systems Journal","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Guilin University of Electronic Technology; Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Relay; Spectral efficiency; Transmission (telecommunications); Computer science; Residual; Mathematical optimization; Optimization problem; Iterative method; Efficient energy use; Power (physics); Interference (communication); Power optimization; Electronic engineering; Mathematics; Computer network; Algorithm; Telecommunications; Engineering; Electrical engineering; Beamforming; Power consumption","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":[0.001002237,0.0005523644,0.0006109125,0.0004263605,0.0003847472,0.001246811,0.0007212624,0.0008607493,0.0007842041],"category_scores_gemma":[0.001935959,0.0003939035,0.0003091652,0.0006041028,0.0006472838,0.001500979,0.0007557005,0.0004471477,0.0001791957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008138295,"about_ca_system_score_gemma":0.0006122117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001321903,"about_ca_topic_score_gemma":0.00124961,"domain_scores_codex":[0.9993485,0.0002701951,0.00002641013,0.0001131211,0.0001618096,0.00008002223],"domain_scores_gemma":[0.999069,0.0006749579,0.00007825136,0.00005561987,0.00009720465,0.0000249345],"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":[0.00009588677,0.00004700296,0.0005047048,0.0001149587,0.0000361831,0.0001919383,0.0001450112,0.9205281,0.01197586,0.03359911,0.0005829378,0.03217835],"study_design_scores_gemma":[0.00001001428,0.00005040758,0.0001689854,0.000006301341,0.000008596254,0.0001072918,0.00003031242,0.9885896,0.001695511,0.008838416,0.0004838802,0.00001068202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09942048,0.001239881,0.8917828,0.0002295692,0.00002546845,0.00003443398,0.00004695489,0.0001526208,0.007067807],"genre_scores_gemma":[0.9555932,0.0006219579,0.04169786,0.00005610959,0.0000157486,0.00005899209,0.00002735059,0.00002186499,0.001906997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001321903,"threshold_uncertainty_score":0.005904734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02533917883068439,"score_gpt":0.2364031458482359,"score_spread":0.2110639670175515,"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."}}