{"id":"W7000224187","doi":"","title":"Efficient Lattice Decoders for the Linear Gaussian Vector Channel: Performance & Complexity Analysis","year":2011,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Decoding methods; MIMO; Lattice (music); Gaussian; Lattice reduction; Computational complexity theory; Wireless; Channel (broadcasting); Communication complexity","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":[0.002879324,0.001209935,0.001129625,0.0009396837,0.0006058802,0.002459737,0.001075699,0.001124343,0.003503013],"category_scores_gemma":[0.01358554,0.000441526,0.0005481727,0.001390189,0.001590202,0.003014541,0.001547585,0.001966074,0.001328021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002348489,"about_ca_system_score_gemma":0.003077805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002716932,"about_ca_topic_score_gemma":0.003339263,"domain_scores_codex":[0.9968517,0.0009955314,0.0001247759,0.0002433613,0.001469816,0.0003147486],"domain_scores_gemma":[0.9917311,0.006040408,0.0004492653,0.000542269,0.001080641,0.0001562627],"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":[0.0001788212,0.00006219,0.0004954341,0.0001208102,0.00003511548,0.00006146148,0.0001187463,0.745094,0.004706556,0.1993906,0.002435191,0.04730117],"study_design_scores_gemma":[0.000008186917,0.00002593634,0.00004665999,0.000009383411,0.000003336279,0.00003120429,0.0000131416,0.974896,0.001757689,0.02272594,0.0004718271,0.00001059769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02233804,0.0006727441,0.9676265,0.0004350373,0.00005771087,0.00008552997,0.000211062,0.0003261472,0.008247169],"genre_scores_gemma":[0.5828969,0.00232385,0.4039682,0.0003372919,0.0002517916,0.0004090584,0.0008262609,0.0002799805,0.008706604],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003503013,"threshold_uncertainty_score":0.01703954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02938179547990255,"score_gpt":0.238690677707521,"score_spread":0.2093088822276185,"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."}}