{"id":"W3084353073","doi":"10.1109/tcomm.2020.3022349","title":"Proactive Eavesdropping via Jamming in Full-Duplex Multi-Antenna Systems: Beamforming Design and Antenna Selection","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Eavesdropping; Beamforming; Computer science; Antenna (radio); Jamming; Physical layer; Optimization problem; Electronic engineering; Mathematical optimization; Algorithm; Telecommunications; Engineering; Computer network; Mathematics; Wireless","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003029995,0.0003634381,0.0003917742,0.0004144319,0.0007192476,0.000123712,0.000847482,0.0001888141,0.00001163779],"category_scores_gemma":[0.00003225522,0.000431162,0.00009535933,0.001158665,0.0001757559,0.0006173213,0.000020647,0.001165015,0.00004323564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003456522,"about_ca_system_score_gemma":0.00006851122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002441215,"about_ca_topic_score_gemma":0.000488935,"domain_scores_codex":[0.9979808,0.0003479276,0.0006864516,0.0003646935,0.0001956335,0.0004244657],"domain_scores_gemma":[0.9977672,0.0005959113,0.0001110489,0.001178246,0.0001444778,0.0002031316],"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":[0.00003340835,0.0001900676,0.00002549906,0.00007819013,0.0001486348,0.000001339041,0.004037876,0.8769706,0.1127703,0.00005721018,0.00001064951,0.00567613],"study_design_scores_gemma":[0.0006766993,0.0001042329,0.0001888204,0.0001884824,0.00007397229,0.00003678775,0.001571631,0.9936799,0.002848568,0.000002114751,0.0002245956,0.0004042361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04310222,0.0009222398,0.9529735,0.0008657715,0.0001639355,0.001173336,0.00002933773,0.0007226806,0.00004696526],"genre_scores_gemma":[0.9313388,0.001587198,0.06612656,0.00006576455,0.00002205249,0.0007187439,0.00001650003,0.00009616627,0.00002822673],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8882366,"threshold_uncertainty_score":0.999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06018245510937005,"score_gpt":0.2546747321788331,"score_spread":0.1944922770694631,"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."}}