{"id":"W2786217313","doi":"10.1109/pimrc.2017.8292406","title":"Joint design of beam selection and precoding for mmWave MU-MIMO systems with lens antenna array","year":2017,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Precoding; MIMO; Computer science; Telecommunications link; Zero-forcing precoding; Antenna (radio); Electronic engineering; Optimization problem; Transmitter; Multi-user MIMO; Algorithm; Telecommunications; Beamforming; Engineering; Channel (broadcasting)","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":[0.0003983892,0.0007548415,0.0005724388,0.0002293669,0.0002165366,0.0006261184,0.0004924874,0.0005388637,0.001063608],"category_scores_gemma":[0.001050246,0.0003506735,0.0003642922,0.0005140878,0.0003838057,0.0006923048,0.0006529111,0.0005575643,0.0004214353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002935874,"about_ca_system_score_gemma":0.0007510608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007597501,"about_ca_topic_score_gemma":0.001158316,"domain_scores_codex":[0.9996111,0.000140205,0.00001640104,0.0000641918,0.0001161849,0.00005195606],"domain_scores_gemma":[0.9995908,0.0001608961,0.00008341456,0.00003883939,0.00009301565,0.00003294546],"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":[0.0003624328,0.0001373176,0.001425839,0.0002051763,0.0001222706,0.0001856401,0.0001320303,0.7049534,0.06793972,0.0287125,0.002733594,0.1930901],"study_design_scores_gemma":[0.00001878716,0.00009244718,0.0001332201,0.000005643511,0.000009157806,0.00005505994,0.00001819674,0.9909855,0.005769919,0.002131246,0.0007708235,0.00001004831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009311669,0.0001078578,0.9893366,0.00007765864,0.00001667157,0.00001621899,0.00002319572,0.00007290389,0.001037169],"genre_scores_gemma":[0.4899456,0.0005323665,0.5062136,0.0001779298,0.00006403399,0.0001872275,0.0001407929,0.00003175519,0.002706699],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001063608,"threshold_uncertainty_score":0.003558159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07161936468517434,"score_gpt":0.2314078395480323,"score_spread":0.159788474862858,"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."}}