{"id":"W2133033435","doi":"10.1109/iscas.2009.5117678","title":"A low-complexity high-speed QR decomposition implementation for MIMO receivers","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"QR decomposition; Computer science; MIMO; CORDIC; Matrix decomposition; Throughput; Parallel computing; Signal processing; Computational complexity theory; Algorithm; Channel (broadcasting); Field-programmable gate array; Computer hardware; Digital signal processing; Wireless; Telecommunications","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":[0.00006398217,0.0001003055,0.0001041079,0.00007330569,0.00007490144,0.00001994245,0.0001504991,0.00004079023,0.0001025824],"category_scores_gemma":[0.000004197278,0.0001124044,0.00003961281,0.0001017282,0.00001551338,0.0002410829,0.00001037375,0.00005996377,0.000009939424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303951,"about_ca_system_score_gemma":0.000004679815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001919729,"about_ca_topic_score_gemma":0.00004152377,"domain_scores_codex":[0.9994725,0.00001313203,0.000190507,0.000105361,0.00006793415,0.0001505726],"domain_scores_gemma":[0.9995877,0.00003634879,0.00003302348,0.0002538211,0.00005308767,0.00003598203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005901501,0.0001067073,0.00005943204,0.00007272855,0.00003443044,6.432743e-7,0.0003564513,0.009545132,0.4201886,0.1081682,0.01368427,0.4477244],"study_design_scores_gemma":[0.0008925927,0.0001445776,0.004812586,0.00002388163,0.00001270187,0.000001758958,0.0001708466,0.02204355,0.9163133,0.05254709,0.002708801,0.0003283177],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1240513,0.0000286594,0.8703774,0.0005662303,0.00006619128,0.000611993,0.00002519127,0.001682815,0.002590257],"genre_scores_gemma":[0.8106972,0.00006592298,0.1888333,0.000138372,0.0000210562,0.00002771243,0.0001808876,0.00001342372,0.00002211109],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6866459,"threshold_uncertainty_score":0.458372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256350010887241,"score_gpt":0.329357205724765,"score_spread":0.3067937056158925,"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."}}