{"id":"W2075357945","doi":"10.1109/itw.2014.6970892","title":"Dirty interference cancellation for Gaussian broadcast channels","year":2014,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transmitter; Channel (broadcasting); Computer science; Interference (communication); Transmission (telecommunications); Gaussian; Computer network; Channel state information; Focus (optics); Topology (electrical circuits); Telecommunications; Independent and identically distributed random variables; Mathematics; Wireless; Engineering; Random variable; Electrical engineering; Physics","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":[0.002463094,0.001423212,0.001202616,0.001308857,0.001231069,0.002500763,0.001435854,0.001333999,0.002861998],"category_scores_gemma":[0.009554119,0.000695838,0.0005992816,0.001566363,0.003536523,0.002221931,0.00200551,0.001781531,0.0008263041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003296116,"about_ca_system_score_gemma":0.002208434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006276701,"about_ca_topic_score_gemma":0.005222179,"domain_scores_codex":[0.9971704,0.0007061241,0.00005408795,0.0003043712,0.001208357,0.000556673],"domain_scores_gemma":[0.9904402,0.006513494,0.0008560732,0.0005491962,0.001466304,0.0001746741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002409851,0.00004877516,0.0005630946,0.000317614,0.00005727017,0.000410504,0.0003790773,0.698034,0.006140771,0.2636939,0.004031889,0.02608209],"study_design_scores_gemma":[0.00001545106,0.00005013961,0.0001110684,0.00003021754,0.00001671602,0.0001514942,0.00006449982,0.9281964,0.001993133,0.0675156,0.001819439,0.00003580704],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02210874,0.001403421,0.9574146,0.0004376859,0.0001183345,0.0000366106,0.0001365712,0.0002914636,0.01805258],"genre_scores_gemma":[0.9246826,0.003253478,0.05878992,0.0003197519,0.0002431882,0.0001504351,0.0002246679,0.0001229811,0.01221298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006276701,"threshold_uncertainty_score":0.02391517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01765377264402502,"score_gpt":0.2479972271782512,"score_spread":0.2303434545342261,"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."}}