{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:HQL36IIFIDDFMKFGAIINCPJTGG","short_pith_number":"pith:HQL36IIF","schema_version":"1.0","canonical_sha256":"3c17bf210540c65628a60210d13d3331ba727516e9448be96efa15d69cde1258","source":{"kind":"arxiv","id":"1901.06650","version":1},"attestation_state":"computed","paper":{"title":"Fading Model Deviation in The NLOS Communication Channel in Limited Reflection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Mohammad Khajezadeh, Paeiz Azmi, Zabihollah Hasanshahi","submitted_at":"2019-01-20T09:58:05Z","abstract_excerpt":"Statistical models are employed to characterize the clutter in the radar and the reflective signals of the telecommunication receivers. End to this, Rayliegh distribution is the simplest fading models in NLOS channels possessing low-accuracy in the high-resolution radars and distant telecommunication receivers. At present, high accuracy models such as the m-type Nakagami and hybrid GG distributions are utilized in order to model fading. However, despite the Non-Rayliegh models have better precision in the NLOS relative to the Rayliegh models, the accuracy of these models decreases when the rad"},"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":"1901.06650","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-01-20T09:58:05Z","cross_cats_sorted":[],"title_canon_sha256":"61644f8e6359a60b0de328457347ce427c3dff375e6a87986e56754011c1f52d","abstract_canon_sha256":"f8320d1e00c16a49828ee66fc17489e7b08e6cfb00406f5a64e5eea85583d04c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:49.541612Z","signature_b64":"ja4WDVIB8EPlzG3/Rt2JplFJB6LlqIaG1cp9CTNLB3VD0qWKJsKyEQGwMubxmiIVeLQXjXjFa2LOn7CNrbexCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c17bf210540c65628a60210d13d3331ba727516e9448be96efa15d69cde1258","last_reissued_at":"2026-05-17T23:55:49.540733Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:49.540733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fading Model Deviation in The NLOS Communication Channel in Limited Reflection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Mohammad Khajezadeh, Paeiz Azmi, Zabihollah Hasanshahi","submitted_at":"2019-01-20T09:58:05Z","abstract_excerpt":"Statistical models are employed to characterize the clutter in the radar and the reflective signals of the telecommunication receivers. End to this, Rayliegh distribution is the simplest fading models in NLOS channels possessing low-accuracy in the high-resolution radars and distant telecommunication receivers. At present, high accuracy models such as the m-type Nakagami and hybrid GG distributions are utilized in order to model fading. However, despite the Non-Rayliegh models have better precision in the NLOS relative to the Rayliegh models, the accuracy of these models decreases when the rad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.06650","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":""},"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":"1901.06650","created_at":"2026-05-17T23:55:49.540880+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.06650v1","created_at":"2026-05-17T23:55:49.540880+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.06650","created_at":"2026-05-17T23:55:49.540880+00:00"},{"alias_kind":"pith_short_12","alias_value":"HQL36IIFIDDF","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"HQL36IIFIDDFMKFG","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"HQL36IIF","created_at":"2026-05-18T12:33:18.533446+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/HQL36IIFIDDFMKFGAIINCPJTGG","json":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG.json","graph_json":"https://pith.science/api/pith-number/HQL36IIFIDDFMKFGAIINCPJTGG/graph.json","events_json":"https://pith.science/api/pith-number/HQL36IIFIDDFMKFGAIINCPJTGG/events.json","paper":"https://pith.science/paper/HQL36IIF"},"agent_actions":{"view_html":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG","download_json":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG.json","view_paper":"https://pith.science/paper/HQL36IIF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.06650&json=true","fetch_graph":"https://pith.science/api/pith-number/HQL36IIFIDDFMKFGAIINCPJTGG/graph.json","fetch_events":"https://pith.science/api/pith-number/HQL36IIFIDDFMKFGAIINCPJTGG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG/action/storage_attestation","attest_author":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG/action/author_attestation","sign_citation":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG/action/citation_signature","submit_replication":"https://pith.science/pith/HQL36IIFIDDFMKFGAIINCPJTGG/action/replication_record"}},"created_at":"2026-05-17T23:55:49.540880+00:00","updated_at":"2026-05-17T23:55:49.540880+00:00"}