{"id":"W1968172594","doi":"10.1155/2014/594282","title":"SER Performance of Large Scale OFDM-SDMA Based Cognitive Radio Networks","year":2014,"lang":"en","type":"article","venue":"International Journal of Antennas and Propagation","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"MIMO; Orthogonal frequency-division multiplexing; Base station; Computer science; Beamforming; Cognitive radio; Telecommunications link; Electronic engineering; MIMO-OFDM; Maximal-ratio combining; Interference (communication); Computer network; Channel (broadcasting); Wireless; Telecommunications; Engineering; Fading","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":[0.001680751,0.0007335739,0.0006706636,0.0003919266,0.0004808208,0.000960908,0.0006593685,0.0005595322,0.0004979299],"category_scores_gemma":[0.004111675,0.0002087684,0.0003066834,0.0003626082,0.0009969809,0.0006055707,0.0008983822,0.0004743533,0.00009525764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008969247,"about_ca_system_score_gemma":0.001116526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003741068,"about_ca_topic_score_gemma":0.002749299,"domain_scores_codex":[0.9991145,0.0002840032,0.00002926779,0.0001164606,0.0002623253,0.0001934543],"domain_scores_gemma":[0.9972571,0.001766233,0.0002608865,0.0001560528,0.0004617749,0.00009812436],"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":[0.0003016922,0.00007091398,0.001969573,0.00009911839,0.00006907493,0.0002358706,0.0000698129,0.9582601,0.00934677,0.00755862,0.0004018502,0.0216166],"study_design_scores_gemma":[0.000008639004,0.0001122987,0.0004361363,0.000004067632,0.00001563871,0.00005333685,0.00002830717,0.9965788,0.001579465,0.001077449,0.00009690098,0.000009016194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5117396,0.00149621,0.4768704,0.000298785,0.0001444524,0.00005203412,0.0000681391,0.0003181327,0.009012269],"genre_scores_gemma":[0.994966,0.0001303672,0.004593411,0.00002467363,0.0000084582,0.00001158476,0.00001151601,0.000003143872,0.0002510334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003741068,"threshold_uncertainty_score":0.008888721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004597058932992558,"score_gpt":0.2162295706964872,"score_spread":0.2116325117634946,"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."}}