{"id":"W2606308235","doi":"10.1109/access.2017.2727550","title":"5G Cellular User Equipment: From Theory to Practical Hardware Design","year":2017,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":236,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Jet Propulsion Laboratory; Government of Jiangsu Province; Six Talent Peaks Project in Jiangsu Province; National Natural Science Foundation of China; Natural Sciences and Engineering Research Council of Canada; Georgia Institute of Technology; National Aeronautics and Space Administration","keywords":"MIMO; Computer science; PHY; Physical layer; User equipment; Wireless; Computer architecture; Cellular architecture; Implementation; Computer hardware; Electronic engineering; Channel (broadcasting); Computer network; Telecommunications; Base station; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001882349,0.0001567707,0.0001704861,0.00004798386,0.0001695078,0.0003813427,0.0005538129,0.00009269971,0.0001407904],"category_scores_gemma":[0.0002002842,0.0001577827,0.00003163883,0.00004659783,0.00002121294,0.001268314,0.00006920041,0.0001243405,0.000295394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007566187,"about_ca_system_score_gemma":0.00001652086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002865349,"about_ca_topic_score_gemma":0.0000116953,"domain_scores_codex":[0.9991513,0.00005164499,0.0001869456,0.0002303637,0.0001373934,0.0002423508],"domain_scores_gemma":[0.9988865,0.0001402676,0.00007002066,0.0007326842,0.00005338377,0.0001171212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006907533,0.00003352368,0.00057616,0.00005265978,0.0001057307,0.00009342417,0.0005185159,0.9362,0.0464193,0.0007039545,0.01044538,0.004782299],"study_design_scores_gemma":[0.00123622,0.00005755655,0.001139419,0.0003026643,0.0001112095,0.000007251358,0.0001210742,0.08172273,0.8776507,0.007232978,0.02925166,0.001166559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007144197,0.00007717154,0.988492,0.00008213378,0.001323945,0.0003665052,0.00001585458,0.0002435325,0.002254673],"genre_scores_gemma":[0.956646,0.00001489689,0.04220664,0.00008220504,0.0003898459,0.00007928161,0.000009378652,0.00007194214,0.0004998022],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9495018,"threshold_uncertainty_score":0.6434193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05853724179027928,"score_gpt":0.3264969880009264,"score_spread":0.2679597462106471,"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."}}