{"id":"W1981939710","doi":"10.1007/s00034-004-1005-3","title":"A Multiuser Detection Receiver Using Blind Antenna Array and Adaptive Parallel Interference Cancellation","year":2004,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Single antenna interference cancellation; Computer science; Multiuser detection; Multipath propagation; Rake receiver; Antenna (radio); Additive white Gaussian noise; Rayleigh fading; Interference (communication); Algorithm; Antenna array; Code division multiple access; Electronic engineering; Array processing; Fading; Channel (broadcasting); Telecommunications; Signal processing; Engineering; Decoding methods; Radar","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":[0.0003459747,0.000141279,0.0001836715,0.0001224421,0.0004358675,0.0005539796,0.0002556359,0.00009442083,0.000001089163],"category_scores_gemma":[0.00001653384,0.0001343202,0.00001794893,0.0003899312,0.00009859636,0.0008719819,0.0001111833,0.0002383717,0.000002730414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001240665,"about_ca_system_score_gemma":0.000182606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002531677,"about_ca_topic_score_gemma":0.00007653144,"domain_scores_codex":[0.9987015,0.0001371705,0.0002675988,0.0004087106,0.0002344995,0.0002505769],"domain_scores_gemma":[0.999099,0.00006480319,0.0001705645,0.0002297621,0.0003247366,0.0001111173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000705995,0.00009806899,0.001155806,0.0004893083,0.00005706422,0.00002712472,0.01018358,0.06717482,0.3236302,0.002197169,0.000004371754,0.5949118],"study_design_scores_gemma":[0.0007848528,0.0000610871,0.0009330598,0.0007326608,0.000006847125,0.0001342675,0.0003837464,0.9939923,0.001853813,0.0008509734,0.00004587159,0.0002205548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08139973,0.004710341,0.9133245,0.00006517288,0.00006665735,0.0002184969,7.563235e-7,0.00005860841,0.0001557857],"genre_scores_gemma":[0.9961575,0.0001207924,0.003567719,0.00001874477,0.00007106669,0.00001643999,7.592006e-7,0.00001181428,0.00003520886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9268174,"threshold_uncertainty_score":0.5477421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07222435789919987,"score_gpt":0.2878414401264083,"score_spread":0.2156170822272085,"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."}}