{"id":"W1965255283","doi":"10.1109/bsc.2010.5472969","title":"SNR-based vs. BER-based power allocation for an amplify-and-forward single-relay wireless system with MRC at destination","year":2010,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Relay; Computer science; Wireless; Transmitter power output; Power (physics); Bit error rate; Signal-to-noise ratio (imaging); Maximal-ratio combining; Terminal (telecommunication); Computer network; Telecommunications; Fading; Transmitter; Channel (broadcasting); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005568474,0.0001804491,0.0001703996,0.0001156022,0.0004618914,0.0002597238,0.0005716616,0.0000942242,0.00001506693],"category_scores_gemma":[0.00004191968,0.0001473742,0.00003470249,0.0002972117,0.00007883776,0.000415214,0.00009600563,0.0001518459,0.000009148297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001137769,"about_ca_system_score_gemma":0.0001158802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001559705,"about_ca_topic_score_gemma":0.0009476881,"domain_scores_codex":[0.9987561,0.0001175195,0.0002467473,0.0004237549,0.0002270293,0.00022881],"domain_scores_gemma":[0.9980907,0.0003231078,0.0001462022,0.0008324441,0.0004638234,0.0001436504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004597843,0.0009613157,0.007325839,0.0002319267,0.00006413426,0.00000372498,0.001482428,0.01048394,0.1836139,0.6782504,0.001563042,0.1155595],"study_design_scores_gemma":[0.001168057,0.0005528746,0.001558764,0.00007157137,0.0000116415,0.000008264114,0.0000258361,0.9751779,0.01816107,0.00001928158,0.002951902,0.0002928336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1896132,0.00001460172,0.8069916,0.001291525,0.0001432838,0.0004730139,0.000001922733,0.0003014207,0.001169465],"genre_scores_gemma":[0.9136479,0.000001484841,0.08545561,0.0005498934,0.00002713342,0.0001174323,0.00004385524,0.00001769111,0.0001390132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.964694,"threshold_uncertainty_score":0.6009747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03051221737463342,"score_gpt":0.2602214813396939,"score_spread":0.2297092639650604,"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."}}