{"id":"W2305668531","doi":"10.1109/iccnc.2016.7440606","title":"Energy-efficient full diversity unitary space-time block code designs using QR decomposition","year":2016,"lang":"en","type":"article","venue":"2016 International Conference on Computing, Networking and Communications (ICNC)","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Space–time block code; Quadrature amplitude modulation; Block code; Computer science; Diversity gain; QR decomposition; Algorithm; QAM; Transmitter; MIMO; Transmit diversity; Electronic engineering; Unitary state; Coding gain; Topology (electrical circuits); Theoretical computer science; Mathematics; Telecommunications; Bit error rate; Channel (broadcasting); Decoding methods; Fading; Physics; Engineering","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":[0.0006875133,0.0009136421,0.0007299748,0.0004416388,0.0002925199,0.0007270953,0.000599335,0.0005963597,0.001774036],"category_scores_gemma":[0.002201865,0.0003071399,0.0004086251,0.0008893069,0.0005877348,0.0008241974,0.0008374031,0.0006964413,0.0007105789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003767397,"about_ca_system_score_gemma":0.0008737164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006006889,"about_ca_topic_score_gemma":0.0007533708,"domain_scores_codex":[0.9991325,0.0003490548,0.00003937201,0.00008713332,0.0003188341,0.00007305612],"domain_scores_gemma":[0.9992459,0.0002321097,0.0001153651,0.0001109712,0.0002579733,0.00003772918],"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":[0.0003437656,0.00009570132,0.0005972857,0.0003340849,0.00009094174,0.0002665899,0.0002396648,0.3570414,0.1043305,0.2917842,0.003182557,0.2416934],"study_design_scores_gemma":[0.00005216511,0.0002715477,0.0001639543,0.00003442238,0.00001840255,0.0003255583,0.00002829257,0.9473633,0.02256171,0.02517541,0.00395749,0.00004782668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007147872,0.0002576057,0.9905916,0.00006338165,0.00002775678,0.00003214648,0.00003955277,0.00007275894,0.001767245],"genre_scores_gemma":[0.2725915,0.0006509189,0.7240397,0.000120432,0.000052315,0.0001635278,0.0001752834,0.00004233532,0.002163933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001774036,"threshold_uncertainty_score":0.005934775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06713440127394812,"score_gpt":0.2971143648131268,"score_spread":0.2299799635391786,"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."}}