{"id":"W2958055639","doi":"10.1109/icc.2019.8761293","title":"Asymptotic BER Analysis of MMSE Receivers in Multicell MU-MIMO Systems","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"MIMO; Upper and lower bounds; Telecommunications link; Minimum mean square error; Base station; Context (archaeology); Signal-to-noise ratio (imaging); Control theory (sociology); Interference (communication); Computer science; Mathematics; Topology (electrical circuits); Noise (video); Signal-to-interference-plus-noise ratio; Bit error rate; Algorithm; Power (physics); Telecommunications; Statistics; Physics; Estimator; Combinatorics; Decoding methods; Mathematical analysis; Beamforming","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":[0.0001167461,0.0001093206,0.000352596,0.0004667141,0.000005630915,0.000009182342,0.00008823063,0.00007473091,0.0001407136],"category_scores_gemma":[0.00001710118,0.0001089954,0.00006400349,0.0009812479,0.000008013727,0.0001559554,0.00001177998,0.00006348018,0.0001220361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143607,"about_ca_system_score_gemma":0.000005287366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002101212,"about_ca_topic_score_gemma":0.0002011533,"domain_scores_codex":[0.9992158,0.000025585,0.0003519854,0.000150151,0.0001009388,0.0001555326],"domain_scores_gemma":[0.9995093,0.00007520858,0.00005535077,0.0002776051,0.00004732903,0.00003520023],"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":[0.000002745597,0.00001054624,0.01578584,0.000110203,0.0001773501,8.795743e-7,0.0001764901,0.9803327,0.003149674,0.0001675919,0.00001590821,0.00007006762],"study_design_scores_gemma":[0.0002547042,0.000009124369,0.002110811,0.0000428712,0.0001130873,2.623449e-7,0.0003289137,0.9962615,0.0006496453,0.000001784786,0.0000992745,0.0001279755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7908579,0.0003321573,0.1751646,0.000005286679,0.0006868939,0.0007056125,0.00001195881,0.0002665365,0.03196909],"genre_scores_gemma":[0.9956846,0.00002545715,0.002499945,0.00000298083,0.000008765917,0.000008832963,0.00001554403,0.00002229115,0.001731596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2048268,"threshold_uncertainty_score":0.4444703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004752348537047267,"score_gpt":0.1978156917222406,"score_spread":0.1930633431851934,"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."}}