{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:YBKWSGVTW7DHRSU4OXFCH6WMOY","short_pith_number":"pith:YBKWSGVT","schema_version":"1.0","canonical_sha256":"c055691ab3b7c678ca9c75ca23facc76155a3a78cc1875d72d3cf4501ca01179","source":{"kind":"arxiv","id":"2211.06995","version":1},"attestation_state":"computed","paper":{"title":"Adaptive Learning-Based Detection for One-Bit Quantized Massive MIMO Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"eess.SP","authors_text":"Brian L. Evans, Jinseok Choi, Yunseong Cho","submitted_at":"2022-11-13T19:12:58Z","abstract_excerpt":"We propose an adaptive learning-based framework for uplink massive multiple-input multiple-output (MIMO) systems with one-bit analog-to-digital converters. Learning-based detection does not need to estimate channels, which overcomes a key drawback in one-bit quantized systems. During training, learning-based detection suffers at high signal-to-noise ratio (SNR) because observations will be biased to +1 or -1 which leads to many zero-valued empirical likelihood functions. At low SNR, observations vary frequently in value but the high noise power makes capturing the effect of the channel difficu"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2211.06995","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2022-11-13T19:12:58Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"11d9d7f620feef3474e7a0a49f5b844798d98372d51ef54ffbb47e29084eb1f2","abstract_canon_sha256":"55a6a4b9a8f209d082071d4100a02cae3922b6c4213547fab524c1d3ad40ad41"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:48.367409Z","signature_b64":"56np0h+L0GO/nKnM03FcV5xRqZmkGAm3WOINHBNi+G7dKS4cgtZXFn8hmyDo0f2FAgnnn9WyFz2KbskImRyZCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c055691ab3b7c678ca9c75ca23facc76155a3a78cc1875d72d3cf4501ca01179","last_reissued_at":"2026-07-05T05:15:48.366846Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:48.366846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adaptive Learning-Based Detection for One-Bit Quantized Massive MIMO Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"eess.SP","authors_text":"Brian L. Evans, Jinseok Choi, Yunseong Cho","submitted_at":"2022-11-13T19:12:58Z","abstract_excerpt":"We propose an adaptive learning-based framework for uplink massive multiple-input multiple-output (MIMO) systems with one-bit analog-to-digital converters. Learning-based detection does not need to estimate channels, which overcomes a key drawback in one-bit quantized systems. During training, learning-based detection suffers at high signal-to-noise ratio (SNR) because observations will be biased to +1 or -1 which leads to many zero-valued empirical likelihood functions. At low SNR, observations vary frequently in value but the high noise power makes capturing the effect of the channel difficu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06995","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2211.06995/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2211.06995","created_at":"2026-07-05T05:15:48.366900+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.06995v1","created_at":"2026-07-05T05:15:48.366900+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06995","created_at":"2026-07-05T05:15:48.366900+00:00"},{"alias_kind":"pith_short_12","alias_value":"YBKWSGVTW7DH","created_at":"2026-07-05T05:15:48.366900+00:00"},{"alias_kind":"pith_short_16","alias_value":"YBKWSGVTW7DHRSU4","created_at":"2026-07-05T05:15:48.366900+00:00"},{"alias_kind":"pith_short_8","alias_value":"YBKWSGVT","created_at":"2026-07-05T05:15:48.366900+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY","json":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY.json","graph_json":"https://pith.science/api/pith-number/YBKWSGVTW7DHRSU4OXFCH6WMOY/graph.json","events_json":"https://pith.science/api/pith-number/YBKWSGVTW7DHRSU4OXFCH6WMOY/events.json","paper":"https://pith.science/paper/YBKWSGVT"},"agent_actions":{"view_html":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY","download_json":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY.json","view_paper":"https://pith.science/paper/YBKWSGVT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.06995&json=true","fetch_graph":"https://pith.science/api/pith-number/YBKWSGVTW7DHRSU4OXFCH6WMOY/graph.json","fetch_events":"https://pith.science/api/pith-number/YBKWSGVTW7DHRSU4OXFCH6WMOY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY/action/storage_attestation","attest_author":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY/action/author_attestation","sign_citation":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY/action/citation_signature","submit_replication":"https://pith.science/pith/YBKWSGVTW7DHRSU4OXFCH6WMOY/action/replication_record"}},"created_at":"2026-07-05T05:15:48.366900+00:00","updated_at":"2026-07-05T05:15:48.366900+00:00"}