{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:WL2M7WSPTTN2D25XAH67ET43PX","short_pith_number":"pith:WL2M7WSP","schema_version":"1.0","canonical_sha256":"b2f4cfda4f9cdba1ebb701fdf24f9b7dc5fc7996ac9c763664368c9ec3bdfb3c","source":{"kind":"arxiv","id":"2408.09394","version":1},"attestation_state":"computed","paper":{"title":"GRLinQ: An Intelligent Spectrum Sharing Mechanism for Device-to-Device Communications with Graph Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT"],"primary_cat":"cs.NI","authors_text":"Chung-Shou Liao, Le Liang, Shi Jin, Xinping Yi, Zhiwei Shan","submitted_at":"2024-08-18T07:39:01Z","abstract_excerpt":"Device-to-device (D2D) spectrum sharing in wireless communications is a challenging non-convex combinatorial optimization problem, involving entangled link scheduling and power control in a large-scale network. The state-of-the-art methods, either from a model-based or a data-driven perspective, exhibit certain limitations such as the critical need for channel state information (CSI) and/or a large number of (solved) instances (e.g., network layouts) as training samples. To advance this line of research, we propose a novel hybrid model/datadriven spectrum sharing mechanism with graph reinforce"},"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":"2408.09394","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NI","submitted_at":"2024-08-18T07:39:01Z","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"title_canon_sha256":"b46a0f966339ce685bcfe00cfba500f8f091b15ef4ab8ea5c0ea85d7a9bee5b7","abstract_canon_sha256":"3b471ca3cb1c973b02a9d73a63433660e58ddd219ff7a998b6c09a862fee30e4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:56:49.110971Z","signature_b64":"TUTeRgxuTM2GKO6rVi5IFnV89xQpywblfG/6Cw5jgwZO5VMFIHrSJWRGZonyP2GQfV2mpz0w6GiddHVQixbVAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2f4cfda4f9cdba1ebb701fdf24f9b7dc5fc7996ac9c763664368c9ec3bdfb3c","last_reissued_at":"2026-07-05T08:56:49.110530Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:56:49.110530Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GRLinQ: An Intelligent Spectrum Sharing Mechanism for Device-to-Device Communications with Graph Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT"],"primary_cat":"cs.NI","authors_text":"Chung-Shou Liao, Le Liang, Shi Jin, Xinping Yi, Zhiwei Shan","submitted_at":"2024-08-18T07:39:01Z","abstract_excerpt":"Device-to-device (D2D) spectrum sharing in wireless communications is a challenging non-convex combinatorial optimization problem, involving entangled link scheduling and power control in a large-scale network. The state-of-the-art methods, either from a model-based or a data-driven perspective, exhibit certain limitations such as the critical need for channel state information (CSI) and/or a large number of (solved) instances (e.g., network layouts) as training samples. To advance this line of research, we propose a novel hybrid model/datadriven spectrum sharing mechanism with graph reinforce"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.09394","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/2408.09394/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":"2408.09394","created_at":"2026-07-05T08:56:49.110585+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.09394v1","created_at":"2026-07-05T08:56:49.110585+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.09394","created_at":"2026-07-05T08:56:49.110585+00:00"},{"alias_kind":"pith_short_12","alias_value":"WL2M7WSPTTN2","created_at":"2026-07-05T08:56:49.110585+00:00"},{"alias_kind":"pith_short_16","alias_value":"WL2M7WSPTTN2D25X","created_at":"2026-07-05T08:56:49.110585+00:00"},{"alias_kind":"pith_short_8","alias_value":"WL2M7WSP","created_at":"2026-07-05T08:56:49.110585+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/WL2M7WSPTTN2D25XAH67ET43PX","json":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX.json","graph_json":"https://pith.science/api/pith-number/WL2M7WSPTTN2D25XAH67ET43PX/graph.json","events_json":"https://pith.science/api/pith-number/WL2M7WSPTTN2D25XAH67ET43PX/events.json","paper":"https://pith.science/paper/WL2M7WSP"},"agent_actions":{"view_html":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX","download_json":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX.json","view_paper":"https://pith.science/paper/WL2M7WSP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.09394&json=true","fetch_graph":"https://pith.science/api/pith-number/WL2M7WSPTTN2D25XAH67ET43PX/graph.json","fetch_events":"https://pith.science/api/pith-number/WL2M7WSPTTN2D25XAH67ET43PX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX/action/storage_attestation","attest_author":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX/action/author_attestation","sign_citation":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX/action/citation_signature","submit_replication":"https://pith.science/pith/WL2M7WSPTTN2D25XAH67ET43PX/action/replication_record"}},"created_at":"2026-07-05T08:56:49.110585+00:00","updated_at":"2026-07-05T08:56:49.110585+00:00"}