{"id":"W4377001514","doi":"10.1109/tcomm.2023.3277033","title":"RSMA Precoding Design Based on Interference Nulling and Sum Rate Upper Bound","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Huawei Technologies","keywords":"Precoding; Upper and lower bounds; Maximization; Mathematical optimization; Mathematics; Zero-forcing precoding; Interference (communication); Computer science; Optimization problem; Algorithm; Topology (electrical circuits); MIMO; Beamforming; Telecommunications; Channel (broadcasting); Statistics; Combinatorics","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":[0.0002595956,0.0001961568,0.0001675257,0.0004517244,0.0005951845,0.00007857848,0.0009157809,0.0001136438,0.00002722426],"category_scores_gemma":[0.00003043901,0.000219234,0.00005471435,0.0006948708,0.0002032319,0.0001995611,0.00001339889,0.0006375813,0.0001375764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081285,"about_ca_system_score_gemma":0.00002285624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006922183,"about_ca_topic_score_gemma":0.00003880581,"domain_scores_codex":[0.999049,0.0001473231,0.0002739256,0.0001929609,0.00009348126,0.0002433102],"domain_scores_gemma":[0.9962323,0.001498822,0.00004267678,0.002119085,0.00005176449,0.00005538688],"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":[0.0000139891,0.00006447767,0.00001222387,0.00002204013,0.00003202567,4.517146e-7,0.0002548756,0.950997,0.005874162,0.0005632141,0.0001655169,0.04200004],"study_design_scores_gemma":[0.0002534852,0.00005804862,0.0001300665,0.0001607211,0.00001493368,0.000001486453,0.000285704,0.9513114,0.04510802,0.001104928,0.001322556,0.000248642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00636898,0.0001769038,0.9878302,0.001498809,0.00016373,0.0003113019,0.00003071412,0.002627598,0.0009917137],"genre_scores_gemma":[0.9732881,0.004390939,0.02169042,0.00006074397,0.000004565259,0.0003682909,0.00001289664,0.00005225303,0.0001318398],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9669191,"threshold_uncertainty_score":0.8940101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06948614300454585,"score_gpt":0.2835017649438014,"score_spread":0.2140156219392556,"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."}}