{"id":"W3004882514","doi":"10.1109/twc.2020.2970002","title":"Joint Impact of I/Q Imbalance and Imperfect CSI on SM-MIMO Systems Over Generalized Beckmann Fading Channels: Optimal Detection and Cramer-Rao Bound","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Cramér–Rao bound; Fading; MIMO; Upper and lower bounds; Pairwise error probability; Channel state information; Algorithm; Computer science; Estimator; Channel (broadcasting); Statistics; Telecommunications; Mathematics; Control theory (sociology); Wireless","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000139982,0.0003564162,0.0005096191,0.0002954588,0.0004832621,0.0001026214,0.0006161484,0.0002064617,0.000008752146],"category_scores_gemma":[0.00002245012,0.0003695046,0.0001508023,0.0005247729,0.0003760596,0.0003408805,0.00002973946,0.0007904635,0.000006321344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002002031,"about_ca_system_score_gemma":0.00002648272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001876058,"about_ca_topic_score_gemma":0.00004672144,"domain_scores_codex":[0.9985038,0.0001580249,0.000538996,0.0003141543,0.0001844293,0.0003006091],"domain_scores_gemma":[0.997717,0.0003393119,0.000170673,0.001533832,0.00009446475,0.0001446924],"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":[0.00006283027,0.0001146169,0.00005041045,0.0001316286,0.0002514936,7.403032e-7,0.001102073,0.8400264,0.1377991,0.0005131665,0.00003097025,0.01991654],"study_design_scores_gemma":[0.0009329458,0.0004021865,0.0007043258,0.0002108488,0.0000597916,0.00001768935,0.0004682265,0.9303018,0.06614581,0.0000606719,0.0002386198,0.0004570593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.670598,0.001767086,0.3257689,0.0003397572,0.000129447,0.0004754439,0.00009948567,0.0007262448,0.00009569558],"genre_scores_gemma":[0.9880012,0.009831953,0.001736426,0.00003155851,0.00002007808,0.0002757116,0.0000113326,0.00007855552,0.00001313432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3240325,"threshold_uncertainty_score":0.9998757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0327310862499523,"score_gpt":0.270773644576399,"score_spread":0.2380425583264467,"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."}}