{"id":"W4409334222","doi":"10.1121/10.0036439","title":"Message passing-based single-carrier communications in deep-sea horizontal acoustic channels: Joint interference cancellation and symbol detection","year":2025,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Science Fund for Distinguished Young Scholars; National Natural Science Foundation of China","keywords":"Maximum a posteriori estimation; Computer science; Algorithm; Joint (building); Interference (communication); Adaptive equalizer; Block (permutation group theory); Multipath propagation; Intersymbol interference; Channel (broadcasting); A priori and a posteriori; Equalization (audio); Acoustics; Physics; Decoding methods; Telecommunications; Mathematics; Maximum likelihood; 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":[0.0005536832,0.0005701442,0.0005224444,0.0003646554,0.0002552497,0.0004710336,0.0006552394,0.0005245641,0.0007241416],"category_scores_gemma":[0.00160015,0.0002333531,0.0003117176,0.0004612173,0.0006377174,0.0008911475,0.0006231539,0.0007052859,0.0003074644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003775605,"about_ca_system_score_gemma":0.00106773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002620975,"about_ca_topic_score_gemma":0.003732593,"domain_scores_codex":[0.9995279,0.00009769,0.0000213279,0.00008228448,0.0002089195,0.00006192292],"domain_scores_gemma":[0.9994996,0.0002200276,0.00006850794,0.00007955128,0.0001109312,0.00002136679],"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":[0.0005000883,0.0001411806,0.002176061,0.0001851058,0.0001401006,0.0001624946,0.0003006606,0.4519924,0.08807068,0.02249197,0.001434139,0.432405],"study_design_scores_gemma":[0.00001959672,0.0001109685,0.0005161668,0.000006626271,0.00002178314,0.00006228984,0.00001527475,0.9659249,0.02987316,0.002019292,0.001416429,0.00001347093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03685387,0.0002297928,0.9616591,0.00007803371,0.0000428262,0.00002238645,0.00001646645,0.0002982965,0.0007991501],"genre_scores_gemma":[0.7114152,0.0003844153,0.2827293,0.0001182747,0.00006980716,0.00007712989,0.0001225376,0.00005179195,0.005031567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002620975,"threshold_uncertainty_score":0.005211473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02144970328412878,"score_gpt":0.236966186130256,"score_spread":0.2155164828461272,"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."}}