{"id":"W2124623546","doi":"10.1109/icc.2011.5963050","title":"Adaptive Localized Resource Allocation with Access Point Coordination in Cellular Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Telecommunications link; Resource allocation; Computer network; Channel allocation schemes; Spectral efficiency; Resource management (computing); Transmission (telecommunications); Cellular network; Channel (broadcasting); Enhanced Data Rates for GSM Evolution; Scheme (mathematics); Orthogonal frequency-division multiplexing; Distributed computing; Wireless; Telecommunications; Mathematics","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":[0.0004285204,0.000376634,0.0004113507,0.0002036474,0.0002942347,0.0003606555,0.0006005908,0.0003593568,0.0003264507],"category_scores_gemma":[0.000947998,0.0001476294,0.0001694277,0.000315537,0.0005692618,0.0004492537,0.0004028101,0.0002574913,0.00007933193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005110092,"about_ca_system_score_gemma":0.0004011748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001833246,"about_ca_topic_score_gemma":0.001819981,"domain_scores_codex":[0.999685,0.0001409462,0.000006933558,0.00005234775,0.00007133151,0.00004342315],"domain_scores_gemma":[0.9997374,0.000152014,0.00003652135,0.00002858308,0.00003027169,0.00001526535],"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":[0.0000852249,0.00003447015,0.000412242,0.00003041113,0.00002888343,0.00009428626,0.00005124652,0.928888,0.008038976,0.01701221,0.0005083848,0.04481559],"study_design_scores_gemma":[0.000008642359,0.00004177806,0.00008938735,0.000001688121,0.000005754976,0.00002445726,0.000006357846,0.9951456,0.000859365,0.00339923,0.000413592,0.000004169032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04136003,0.0006001272,0.9566033,0.00005975654,0.0000284088,0.00001883871,0.000008063934,0.0001083043,0.001213152],"genre_scores_gemma":[0.9561654,0.0002581772,0.04240662,0.00003292798,0.00004409492,0.00004269585,0.00000939693,0.000008870647,0.001031935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001833246,"threshold_uncertainty_score":0.003707647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531551351279732,"score_gpt":0.1997579689758785,"score_spread":0.1844424554630812,"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."}}