{"id":"W2565694439","doi":"10.1109/uemcon.2016.7777914","title":"Optimal beamforming-based power control in wireless body area networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Stackelberg competition; Computer science; Goodput; Computer network; Beamforming; Power control; Wireless; Transmitter power output; Telecommunications link; Nash equilibrium; Game theory; Power (physics); Throughput; Transmitter; Mathematical optimization; Telecommunications; Channel (broadcasting); Mathematics","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":[0.001675974,0.001042141,0.0008435779,0.0005305004,0.0004935264,0.00124126,0.0008343346,0.001145892,0.002315747],"category_scores_gemma":[0.004657981,0.000454702,0.0003976244,0.0006108336,0.002155531,0.001295493,0.001061543,0.0008256807,0.0004512859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176217,"about_ca_system_score_gemma":0.001059938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003050946,"about_ca_topic_score_gemma":0.001993685,"domain_scores_codex":[0.9990846,0.0004307966,0.00003106087,0.00009785184,0.0001896171,0.0001660818],"domain_scores_gemma":[0.9982668,0.001233926,0.0001656477,0.00004651242,0.0002201205,0.00006685065],"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":[0.00006365529,0.00003943271,0.0003131604,0.00005712944,0.00002107399,0.00008671165,0.00009096268,0.9101911,0.003710511,0.0743608,0.0007130336,0.01035244],"study_design_scores_gemma":[0.00001076466,0.00003835556,0.00006580258,0.000007402417,0.000004458142,0.00001623465,0.00001962464,0.9786361,0.0003584788,0.02060225,0.0002332633,0.000007337404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02012475,0.0002943598,0.9708874,0.0003312734,0.00005245452,0.00004170608,0.00003429801,0.00009953472,0.008134181],"genre_scores_gemma":[0.9568158,0.0004533376,0.03856131,0.000141791,0.00004206347,0.0001311177,0.00002541659,0.00003216916,0.003797043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003050946,"threshold_uncertainty_score":0.008863509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004682070408512451,"score_gpt":0.185176298326306,"score_spread":0.1804942279177936,"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."}}