{"id":"W2152262955","doi":"10.1109/wcnc.2008.150","title":"Haar Compression for Efficient CQI Feedback Signaling in 3GPP LTE Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"InterDigital (Canada)","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Computer network; Overhead (engineering); Real-time computing; Throughput; Base station; Channel (broadcasting); Wireless; Engineering; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006724059,0.0001201441,0.0001680098,0.00007829614,0.00006358974,0.00001197795,0.00007522789,0.00006661903,0.00001098431],"category_scores_gemma":[0.000008640835,0.0001155388,0.00002993598,0.0001808525,0.00001380155,0.00007001555,0.00001468524,0.00007705697,0.00001340386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008613648,"about_ca_system_score_gemma":0.000005879294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007247671,"about_ca_topic_score_gemma":0.000002576812,"domain_scores_codex":[0.9992553,0.00001278556,0.0002452638,0.0001450587,0.0001059857,0.0002356012],"domain_scores_gemma":[0.9996843,0.00008381891,0.00002748373,0.0001257457,0.00003464242,0.00004401446],"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":[0.000009175613,0.00001407125,0.0001458463,0.00005730082,0.000004252107,0.000002432848,0.0001134887,0.9949301,0.003771052,0.0001796006,0.0005080684,0.0002646352],"study_design_scores_gemma":[0.0004899656,0.00001122214,0.0000942613,0.0001184827,0.000002267505,0.000004162062,0.00005060992,0.9945621,0.003822364,0.000007991721,0.0006908546,0.0001457325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1846617,0.0005052413,0.8126711,0.000006451864,0.0003749938,0.0004079794,0.000002723796,0.0002992637,0.001070513],"genre_scores_gemma":[0.9829989,0.00005783042,0.01652188,0.000009342411,0.00009665247,0.00005816364,0.00001882471,0.00004064197,0.0001977807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7983372,"threshold_uncertainty_score":0.4711534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529734975105068,"score_gpt":0.2111349664328555,"score_spread":0.1958376166818049,"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."}}