{"id":"W1996911166","doi":"10.1002/ett.2577","title":"Location‐assisted clustering and scheduling for coordinated homogeneous and heterogeneous cellular networks","year":2012,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Base station; Heterogeneous network; Computer science; MIMO; Channel state information; Cellular network; Computer network; Telecommunications link; Scheduling (production processes); Homogeneous; Precoding; Transmission (telecommunications); Transmitter; Spectral efficiency; Real-time computing; Wireless network; Wireless; Channel (broadcasting); Telecommunications; Mathematical optimization; 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":[0.0007030054,0.0004599908,0.0005700638,0.0004541776,0.0005604233,0.0005438593,0.0009079471,0.0004242188,0.0005721898],"category_scores_gemma":[0.001803241,0.0002096251,0.0002260248,0.0007155866,0.0004465403,0.0004383006,0.0006623953,0.0002634912,0.0001456019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597947,"about_ca_system_score_gemma":0.0009667953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01080158,"about_ca_topic_score_gemma":0.008634609,"domain_scores_codex":[0.9995018,0.0001771183,0.00001572511,0.00008394699,0.00009827378,0.0001231218],"domain_scores_gemma":[0.998848,0.000431701,0.0002629481,0.0001426287,0.0001992388,0.0001155398],"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":[0.0001010063,0.000029597,0.0006100195,0.00001542891,0.0000160455,0.0000503437,0.00003223613,0.981257,0.002847424,0.00323381,0.0005184085,0.0112887],"study_design_scores_gemma":[0.000006541612,0.00002482882,0.0001977621,7.157742e-7,0.000003785828,0.00000741923,0.0000120515,0.998113,0.0006060264,0.0008808227,0.0001437685,0.000003169909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.30945,0.0004798275,0.685212,0.0001877644,0.00006195807,0.00007933458,0.0000965423,0.0003762338,0.004056373],"genre_scores_gemma":[0.9804837,0.00006455452,0.01873013,0.00002160786,0.00001234228,0.00002002445,0.00003499791,0.00001139641,0.0006211147],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01080158,"threshold_uncertainty_score":0.0214774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588804566416313,"score_gpt":0.2407474225886459,"score_spread":0.2248593769244828,"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."}}