{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2HE7HT3L5XIWSP3TAO72HRTBS2","short_pith_number":"pith:2HE7HT3L","schema_version":"1.0","canonical_sha256":"d1c9f3cf6bedd1693f7303bfa3c661968cc56a67974e86f8e6d3da8fe7b31552","source":{"kind":"arxiv","id":"1710.08671","version":2},"attestation_state":"computed","paper":{"title":"Linear State Estimation via 5G C-RAN Cellular Networks using Gaussian Belief Propagation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Dejan Vukobratovic, Mirsad Cosovic, Vladimir Stankovic","submitted_at":"2017-10-24T09:27:51Z","abstract_excerpt":"Machine-type communications and large-scale information processing architectures are among key (r)evolutionary enhancements of emerging fifth-generation (5G) mobile cellular networks. Massive data acquisition and processing will make 5G network an ideal platform for large-scale system monitoring and control with applications in future smart transportation, connected industry, power grids, etc. In this work, we investigate a capability of such a 5G network architecture to provide the state estimate of an underlying linear system from the input obtained via large-scale deployment of measurement "},"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":"1710.08671","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2017-10-24T09:27:51Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"60a5c06989fc3027bf02151d443fc522fe989e30595aabb54fd810d4902eb540","abstract_canon_sha256":"df96d00e1a29867ac64084a3614e512d915539fd6502f27f0d649a6b3816980d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:35.100038Z","signature_b64":"NTR/FFM4yr30EuWoBKEQmr77l7d9lTRXZW6o6JqIczgGR8gNXAQItrPmWN9x8xz8PFkF/tpHBfbG9EgGmFfRBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d1c9f3cf6bedd1693f7303bfa3c661968cc56a67974e86f8e6d3da8fe7b31552","last_reissued_at":"2026-05-18T00:24:35.099666Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:35.099666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Linear State Estimation via 5G C-RAN Cellular Networks using Gaussian Belief Propagation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Dejan Vukobratovic, Mirsad Cosovic, Vladimir Stankovic","submitted_at":"2017-10-24T09:27:51Z","abstract_excerpt":"Machine-type communications and large-scale information processing architectures are among key (r)evolutionary enhancements of emerging fifth-generation (5G) mobile cellular networks. Massive data acquisition and processing will make 5G network an ideal platform for large-scale system monitoring and control with applications in future smart transportation, connected industry, power grids, etc. In this work, we investigate a capability of such a 5G network architecture to provide the state estimate of an underlying linear system from the input obtained via large-scale deployment of measurement "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.08671","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1710.08671","created_at":"2026-05-18T00:24:35.099728+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.08671v2","created_at":"2026-05-18T00:24:35.099728+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.08671","created_at":"2026-05-18T00:24:35.099728+00:00"},{"alias_kind":"pith_short_12","alias_value":"2HE7HT3L5XIW","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2HE7HT3L5XIWSP3T","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2HE7HT3L","created_at":"2026-05-18T12:30:55.937587+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/2HE7HT3L5XIWSP3TAO72HRTBS2","json":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2.json","graph_json":"https://pith.science/api/pith-number/2HE7HT3L5XIWSP3TAO72HRTBS2/graph.json","events_json":"https://pith.science/api/pith-number/2HE7HT3L5XIWSP3TAO72HRTBS2/events.json","paper":"https://pith.science/paper/2HE7HT3L"},"agent_actions":{"view_html":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2","download_json":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2.json","view_paper":"https://pith.science/paper/2HE7HT3L","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.08671&json=true","fetch_graph":"https://pith.science/api/pith-number/2HE7HT3L5XIWSP3TAO72HRTBS2/graph.json","fetch_events":"https://pith.science/api/pith-number/2HE7HT3L5XIWSP3TAO72HRTBS2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2/action/storage_attestation","attest_author":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2/action/author_attestation","sign_citation":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2/action/citation_signature","submit_replication":"https://pith.science/pith/2HE7HT3L5XIWSP3TAO72HRTBS2/action/replication_record"}},"created_at":"2026-05-18T00:24:35.099728+00:00","updated_at":"2026-05-18T00:24:35.099728+00:00"}