{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:PCNOKOMSA2IZ6BNTKOZJRZL6VT","short_pith_number":"pith:PCNOKOMS","schema_version":"1.0","canonical_sha256":"789ae5399206919f05b353b298e57eacd5fec16b4329a18bd8a5e8d497bb3611","source":{"kind":"arxiv","id":"1810.04520","version":1},"attestation_state":"computed","paper":{"title":"Deep Reinforcement Learning for Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GT","cs.NI","eess.SP"],"primary_cat":"cs.LG","authors_text":"Dong In Kim, Dusit Niyato, Nguyen Cong Luong, Tran The Anh, Ying-Chang Liang","submitted_at":"2018-10-03T05:30:23Z","abstract_excerpt":"In an RF-powered backscatter cognitive radio network, multiple secondary users communicate with a secondary gateway by backscattering or harvesting energy and actively transmitting their data depending on the primary channel state. To coordinate the transmission of multiple secondary transmitters, the secondary gateway needs to schedule the backscattering time, energy harvesting time, and transmission time among them. However, under the dynamics of the primary channel and the uncertainty of the energy state of the secondary transmitters, it is challenging for the gateway to find a time schedul"},"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":"1810.04520","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-03T05:30:23Z","cross_cats_sorted":["cs.GT","cs.NI","eess.SP"],"title_canon_sha256":"86d741868e1b2b0ab64f8f8272375bbce69dfd9485ac08e3b6587f5b44b418e6","abstract_canon_sha256":"1abd3eb55adaf85e7b7642ec46b88e1e959ff46c9e8fa7d6b1a88a93f8bbd57c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:39.878147Z","signature_b64":"PcBWNMYklqDdzPyyFUh39HJKZZ7CWVpYvz02jAZp0pQcK+7NLZFhrCWAPJPeyZRoqCvx8LxBNVcwsyntzvLeBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"789ae5399206919f05b353b298e57eacd5fec16b4329a18bd8a5e8d497bb3611","last_reissued_at":"2026-05-18T00:03:39.877621Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:39.877621Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Deep Reinforcement Learning for Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GT","cs.NI","eess.SP"],"primary_cat":"cs.LG","authors_text":"Dong In Kim, Dusit Niyato, Nguyen Cong Luong, Tran The Anh, Ying-Chang Liang","submitted_at":"2018-10-03T05:30:23Z","abstract_excerpt":"In an RF-powered backscatter cognitive radio network, multiple secondary users communicate with a secondary gateway by backscattering or harvesting energy and actively transmitting their data depending on the primary channel state. To coordinate the transmission of multiple secondary transmitters, the secondary gateway needs to schedule the backscattering time, energy harvesting time, and transmission time among them. However, under the dynamics of the primary channel and the uncertainty of the energy state of the secondary transmitters, it is challenging for the gateway to find a time schedul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.04520","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":"1810.04520","created_at":"2026-05-18T00:03:39.877708+00:00"},{"alias_kind":"arxiv_version","alias_value":"1810.04520v1","created_at":"2026-05-18T00:03:39.877708+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.04520","created_at":"2026-05-18T00:03:39.877708+00:00"},{"alias_kind":"pith_short_12","alias_value":"PCNOKOMSA2IZ","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_16","alias_value":"PCNOKOMSA2IZ6BNT","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_8","alias_value":"PCNOKOMS","created_at":"2026-05-18T12:32:43.782077+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"1907.10102","citing_title":"Next-generation Wireless Solutions for the Smart Factory, Smart Vehicles, the Smart Grid and Smart Cities","ref_index":188,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT","json":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT.json","graph_json":"https://pith.science/api/pith-number/PCNOKOMSA2IZ6BNTKOZJRZL6VT/graph.json","events_json":"https://pith.science/api/pith-number/PCNOKOMSA2IZ6BNTKOZJRZL6VT/events.json","paper":"https://pith.science/paper/PCNOKOMS"},"agent_actions":{"view_html":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT","download_json":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT.json","view_paper":"https://pith.science/paper/PCNOKOMS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1810.04520&json=true","fetch_graph":"https://pith.science/api/pith-number/PCNOKOMSA2IZ6BNTKOZJRZL6VT/graph.json","fetch_events":"https://pith.science/api/pith-number/PCNOKOMSA2IZ6BNTKOZJRZL6VT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT/action/storage_attestation","attest_author":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT/action/author_attestation","sign_citation":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT/action/citation_signature","submit_replication":"https://pith.science/pith/PCNOKOMSA2IZ6BNTKOZJRZL6VT/action/replication_record"}},"created_at":"2026-05-18T00:03:39.877708+00:00","updated_at":"2026-05-18T00:03:39.877708+00:00"}