{"id":"W1564889342","doi":"10.1109/vetecs.2004.1390550","title":"Trellis coded modulation design for multi-user systems on AWGN channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Trellis modulation; Additive white Gaussian noise; Computer science; Trellis (graph); Constellation; Coding (social sciences); Space–time trellis code; Modulation (music); Channel (broadcasting); Algorithm; Scheme (mathematics); Decoding methods; Theoretical computer science; Electronic engineering; Computer network; Fading; Mathematics; Engineering; Concatenated error correction code; Block code","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":[0.001128678,0.0005040651,0.000385843,0.0005359192,0.0003258164,0.0006063496,0.0004936525,0.0006859648,0.001115781],"category_scores_gemma":[0.003725647,0.0002247307,0.0002614539,0.0007621348,0.0005663483,0.0005773596,0.000379069,0.0006084997,0.0003998634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008625182,"about_ca_system_score_gemma":0.0008136298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001707808,"about_ca_topic_score_gemma":0.001718549,"domain_scores_codex":[0.9989512,0.0004677952,0.00005389502,0.00006781011,0.0003790515,0.00008023436],"domain_scores_gemma":[0.9982136,0.0008785271,0.0002188653,0.0001397634,0.0005132586,0.00003603414],"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":[0.0002841493,0.00005644095,0.0007196948,0.0002645313,0.00005587098,0.0002638523,0.0003363027,0.701292,0.05326833,0.09619302,0.002136658,0.1451291],"study_design_scores_gemma":[0.00003727571,0.0001213098,0.0001623289,0.00002343998,0.00001339085,0.0001132007,0.00001507595,0.9783124,0.008512801,0.01034394,0.002327818,0.00001703993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01105394,0.0003847126,0.9855602,0.0001271823,0.00003383937,0.00005933423,0.00002667928,0.000114714,0.002639391],"genre_scores_gemma":[0.5954935,0.001129936,0.3992164,0.0001591964,0.0001219631,0.0003469458,0.0001050096,0.00006811516,0.003358964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001707808,"threshold_uncertainty_score":0.00625807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07148492262523573,"score_gpt":0.2989529984104952,"score_spread":0.2274680757852595,"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."}}