{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:2GIPP7G6CLU5BWHIJ5S7H7J4AP","short_pith_number":"pith:2GIPP7G6","schema_version":"1.0","canonical_sha256":"d190f7fcde12e9d0d8e84f65f3fd3c03e07dd41db23079f8eb9d19d169aed96e","source":{"kind":"arxiv","id":"2207.01908","version":2},"attestation_state":"computed","paper":{"title":"Phase Shift Compression for Control Signaling Reduction in IRS-Aided Wireless Systems: Global Attention and Lightweight Design","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Dong Li, Xianhua Yu","submitted_at":"2022-07-05T09:38:26Z","abstract_excerpt":"A potential 6G technology known as intelligent reflecting surface (IRS) has recently gained much attention from academia and industry. However, acquiring the optimized quantized phase shift (QPS) presents challenges for the IRS due to the phenomenon of signaling storms. In this paper, we attempt to solve the above problem by proposing two deep learning models, the global attention phase shift compression network (GAPSCN) and the simplified GAPSCN (S-GAPSCN). In GAPSCN, we propose a novel attention mechanism that emphasizes a greater number of meaningful features than previous attention-related"},"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":"2207.01908","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-07-05T09:38:26Z","cross_cats_sorted":[],"title_canon_sha256":"046c3b648d4f99faaee7e8b6bb7fc902cc2c00a8801dcbce5fdf4f20cbe862ea","abstract_canon_sha256":"798ed824f56badefc68bce7ec5c29e954fc41b872a600fc7de93f6964f391fbb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:09:04.972430Z","signature_b64":"U6h6j2OWz0m3JzHLEOECiSCrYSSDbjkEcZmYhqfbxf52aTY8DEUV1hummrOFbBolQ370s9lK74fah0wGQm/ABA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d190f7fcde12e9d0d8e84f65f3fd3c03e07dd41db23079f8eb9d19d169aed96e","last_reissued_at":"2026-07-05T06:09:04.972042Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:09:04.972042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Phase Shift Compression for Control Signaling Reduction in IRS-Aided Wireless Systems: Global Attention and Lightweight Design","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Dong Li, Xianhua Yu","submitted_at":"2022-07-05T09:38:26Z","abstract_excerpt":"A potential 6G technology known as intelligent reflecting surface (IRS) has recently gained much attention from academia and industry. However, acquiring the optimized quantized phase shift (QPS) presents challenges for the IRS due to the phenomenon of signaling storms. In this paper, we attempt to solve the above problem by proposing two deep learning models, the global attention phase shift compression network (GAPSCN) and the simplified GAPSCN (S-GAPSCN). In GAPSCN, we propose a novel attention mechanism that emphasizes a greater number of meaningful features than previous attention-related"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01908","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.01908/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":"2207.01908","created_at":"2026-07-05T06:09:04.972101+00:00"},{"alias_kind":"arxiv_version","alias_value":"2207.01908v2","created_at":"2026-07-05T06:09:04.972101+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01908","created_at":"2026-07-05T06:09:04.972101+00:00"},{"alias_kind":"pith_short_12","alias_value":"2GIPP7G6CLU5","created_at":"2026-07-05T06:09:04.972101+00:00"},{"alias_kind":"pith_short_16","alias_value":"2GIPP7G6CLU5BWHI","created_at":"2026-07-05T06:09:04.972101+00:00"},{"alias_kind":"pith_short_8","alias_value":"2GIPP7G6","created_at":"2026-07-05T06:09:04.972101+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/2GIPP7G6CLU5BWHIJ5S7H7J4AP","json":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP.json","graph_json":"https://pith.science/api/pith-number/2GIPP7G6CLU5BWHIJ5S7H7J4AP/graph.json","events_json":"https://pith.science/api/pith-number/2GIPP7G6CLU5BWHIJ5S7H7J4AP/events.json","paper":"https://pith.science/paper/2GIPP7G6"},"agent_actions":{"view_html":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP","download_json":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP.json","view_paper":"https://pith.science/paper/2GIPP7G6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2207.01908&json=true","fetch_graph":"https://pith.science/api/pith-number/2GIPP7G6CLU5BWHIJ5S7H7J4AP/graph.json","fetch_events":"https://pith.science/api/pith-number/2GIPP7G6CLU5BWHIJ5S7H7J4AP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP/action/storage_attestation","attest_author":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP/action/author_attestation","sign_citation":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP/action/citation_signature","submit_replication":"https://pith.science/pith/2GIPP7G6CLU5BWHIJ5S7H7J4AP/action/replication_record"}},"created_at":"2026-07-05T06:09:04.972101+00:00","updated_at":"2026-07-05T06:09:04.972101+00:00"}