{"id":"W2082239820","doi":"10.1002/wcm.403","title":"Tone diversity for OFDMA in broadband wireless communications","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Transmitter; Computer science; Orthogonal frequency-division multiple access; Wireless broadband; Orthogonal frequency-division multiplexing; Code division multiple access; Diversity scheme; Maximal-ratio combining; Tone (literature); Wireless; Equalization (audio); Channel (broadcasting); Computer network; Frequency-division multiple access; Telecommunications; Electronic engineering; Wireless network; Fading; 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":[0.0002918911,0.0002176697,0.0002043993,0.0003216146,0.0003292579,0.0005422884,0.0002299112,0.0004320959,0.001556003],"category_scores_gemma":[0.0007881938,0.0001114918,0.0001420805,0.0003443714,0.0003590237,0.0003663757,0.0004239245,0.0003376479,0.000414839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002133974,"about_ca_system_score_gemma":0.0001633598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002535898,"about_ca_topic_score_gemma":0.0003195242,"domain_scores_codex":[0.9998122,0.00007758147,0.000005328597,0.00001990229,0.00005838763,0.00002660642],"domain_scores_gemma":[0.9997221,0.0001655151,0.00002401379,0.00003219676,0.00004054428,0.00001577087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005116367,0.00009078282,0.001808809,0.0003327961,0.0001050603,0.000588532,0.0002169303,0.07434686,0.1522349,0.1245637,0.004004506,0.6411955],"study_design_scores_gemma":[0.0001148447,0.0008388584,0.001850125,0.00008704482,0.0001457567,0.001718129,0.0001258867,0.7998905,0.06195489,0.08716535,0.04603881,0.00006985802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1188446,0.01217707,0.8505162,0.0007754028,0.0002823535,0.00005708036,0.00005177038,0.0005017922,0.0167937],"genre_scores_gemma":[0.8712808,0.003317755,0.1201921,0.0002683234,0.0003826669,0.00003658207,0.00004417945,0.00002099998,0.004456523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001556003,"threshold_uncertainty_score":0.005205393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02029384459064641,"score_gpt":0.2861399930764381,"score_spread":0.2658461484857917,"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."}}