{"id":"W2170023479","doi":"10.1109/isit.2010.5513347","title":"Interference alignment for the K user MIMO interference channel","year":2010,"lang":"en","type":"preprint","venue":"","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"MIMO; Interference (communication); Transmitter; Topology (electrical circuits); Channel (broadcasting); Upper and lower bounds; Gaussian; Degrees of freedom (physics and chemistry); Combinatorics; Mathematics; Computer science; Algorithm; Telecommunications; Physics; Mathematical analysis","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":[0.0008212313,0.001009971,0.0007119441,0.0003734099,0.0005724936,0.0009671923,0.0004699584,0.0006093,0.00201103],"category_scores_gemma":[0.002334973,0.0002557788,0.0005969671,0.001103627,0.001101566,0.001139463,0.0009881665,0.0008272929,0.0006222489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008476918,"about_ca_system_score_gemma":0.0008420913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001578835,"about_ca_topic_score_gemma":0.001543743,"domain_scores_codex":[0.9989441,0.0003520141,0.00003592308,0.0001252837,0.0003108428,0.0002318082],"domain_scores_gemma":[0.9986151,0.0007571894,0.0002715496,0.0001274977,0.0001752836,0.00005334923],"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":[0.0002346014,0.00003828894,0.001327038,0.000173435,0.00004528986,0.000478525,0.0001974798,0.7857326,0.01276602,0.1750556,0.00171117,0.02223997],"study_design_scores_gemma":[0.00001036241,0.00008417609,0.0006132734,0.00002095696,0.00001888215,0.0002725953,0.00006326753,0.951961,0.003837593,0.04144335,0.001636709,0.00003796188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04014838,0.0007223684,0.9493739,0.0002087213,0.00004451883,0.00002026838,0.0001750257,0.0001137043,0.009193054],"genre_scores_gemma":[0.9118645,0.002147439,0.08127263,0.0001792126,0.000148061,0.0001070278,0.0002502511,0.00005865531,0.003972161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00201103,"threshold_uncertainty_score":0.006727576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02766947863060036,"score_gpt":0.237215940709027,"score_spread":0.2095464620784267,"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."}}