{"id":"W6976610883","doi":"10.60692/bdvg5-wck72","title":"Precoded Large Scale Multi‐User‐MIMO System Using Likelihood Ascent Search for Signal Detection","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Precoding; Base station; User equipment; Interference (communication); Multiuser detection; Spectral efficiency; Detection theory; Joint (building); Bit error rate","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":[0.0004729121,0.0004669546,0.0007460571,0.0002387117,0.0003362652,0.000654319,0.0005077801,0.0004602629,0.001466964],"category_scores_gemma":[0.001147559,0.0001897024,0.0003212898,0.0004663506,0.0004189676,0.0005566743,0.0005465843,0.0005067181,0.0003235093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005723507,"about_ca_system_score_gemma":0.001337726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003346073,"about_ca_topic_score_gemma":0.003902231,"domain_scores_codex":[0.9996214,0.0001319216,0.00001321267,0.000055646,0.0001314932,0.0000463272],"domain_scores_gemma":[0.9995618,0.0002367017,0.00005132609,0.0000345053,0.00009267093,0.00002283014],"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":[0.0004579665,0.0001794317,0.001323369,0.0001266662,0.00007047344,0.0002102679,0.0001175006,0.8281406,0.0238556,0.01417744,0.001768609,0.1295721],"study_design_scores_gemma":[0.000008532974,0.00004125755,0.00005411532,0.000002337337,0.000002952327,0.00001676827,0.000004962907,0.997968,0.001410751,0.0003129197,0.0001733538,0.000004007414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07558846,0.0003003228,0.9200082,0.0002509909,0.00005554793,0.00004906003,0.00005102919,0.0003742589,0.003322095],"genre_scores_gemma":[0.8410307,0.0001398092,0.1550143,0.00008384094,0.00002347556,0.00007799534,0.00008012429,0.00001227916,0.003537379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003346073,"threshold_uncertainty_score":0.00665319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02415771348478084,"score_gpt":0.2204948759958396,"score_spread":0.1963371625110587,"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."}}