{"id":"W2742633106","doi":"10.1109/twc.2017.2734772","title":"Nonlinear MIMO Transceivers Improve Wireless-Powered and Self-Interference-Aided Relaying","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Relay; Computer science; Transceiver; Robustness (evolution); MIMO; Precoding; Transmitter power output; Control theory (sociology); Wireless; Channel state information; Mathematical optimization; Channel (broadcasting); Power (physics); Mathematics; Telecommunications; 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":[0.0005729678,0.0007285602,0.0004114614,0.0001790319,0.0001716858,0.0006127517,0.0005319929,0.0006960429,0.001187796],"category_scores_gemma":[0.001596896,0.0002496137,0.0003283688,0.0001721443,0.0004399449,0.0007149288,0.0004915616,0.0005502819,0.0005641978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003552025,"about_ca_system_score_gemma":0.000318618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000339742,"about_ca_topic_score_gemma":0.0004040716,"domain_scores_codex":[0.9996841,0.00007382083,0.00001727087,0.00005630864,0.0001395565,0.00002893088],"domain_scores_gemma":[0.9993572,0.0003082672,0.0001350111,0.00005350636,0.0001313532,0.00001465823],"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":[0.0000658428,0.00006431731,0.0005538223,0.0001895514,0.00005172635,0.0001997786,0.0001824133,0.8122783,0.07589041,0.04999635,0.0006168925,0.05991063],"study_design_scores_gemma":[0.000008825408,0.0001506744,0.0001639323,0.00001187083,0.00001577927,0.00008470367,0.0000161469,0.9838102,0.01001695,0.003672918,0.002033079,0.00001487484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01752224,0.000383007,0.9757153,0.00009421326,0.00003893475,0.0000276104,0.00001435252,0.000129263,0.006075074],"genre_scores_gemma":[0.8597969,0.0007947139,0.1336068,0.0001125595,0.00008237857,0.00008825246,0.00004682978,0.00004346986,0.005427989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001187796,"threshold_uncertainty_score":0.003973603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02183113827368625,"score_gpt":0.2513477034675751,"score_spread":0.2295165651938888,"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."}}