{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:QMVA3BYVM25UXKLX6DNEX2JUZR","short_pith_number":"pith:QMVA3BYV","schema_version":"1.0","canonical_sha256":"832a0d871566bb4ba977f0da4be934cc4330e14acbd868e1ceaad812c7f75e0f","source":{"kind":"arxiv","id":"2503.09489","version":1},"attestation_state":"computed","paper":{"title":"Optimal ISAC Beamforming Structure and Efficient Algorithms for Sum Rate and CRLB Balancing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"A. Lee Swindlehurst, Markku Juntti, Mengyuan Ma, Nhan Thanh Nguyen, Nir Shlezinger, Tianyu Fang","submitted_at":"2025-03-12T15:48:35Z","abstract_excerpt":"Integrated sensing and communications (ISAC) has emerged as a promising paradigm to unify wireless communications and radar sensing, enabling efficient spectrum and hardware utilization. A core challenge with realizing the gains of ISAC stems from the unique challenges of dual purpose beamforming design due to the highly non-convex nature of key performance metrics such as sum rate for communications and the Cramer-Rao lower bound (CRLB) for sensing. In this paper, we propose a low-complexity structured approach to ISAC beamforming optimization to simultaneously enhance spectral efficiency and"},"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":"2503.09489","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-03-12T15:48:35Z","cross_cats_sorted":["eess.SP","math.IT"],"title_canon_sha256":"514f5892210cbbda21053f1424f126cd6ff8e8e916c6f91d1ef137b2a1811ae2","abstract_canon_sha256":"dc1b028c6aff8e706f70eaf27584acec24a3993362b684aac4c4601b03e1a8d2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:29:57.090215Z","signature_b64":"JhJsytmIR72xNUi3/iIPKYA3ho62fqNfUR0EWiwVyMRXeg5uHmWFU7oCe7bkVGQKOJs7z5sinWjr7fG5n7v2Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"832a0d871566bb4ba977f0da4be934cc4330e14acbd868e1ceaad812c7f75e0f","last_reissued_at":"2026-07-05T10:29:57.089572Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:29:57.089572Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimal ISAC Beamforming Structure and Efficient Algorithms for Sum Rate and CRLB Balancing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"A. Lee Swindlehurst, Markku Juntti, Mengyuan Ma, Nhan Thanh Nguyen, Nir Shlezinger, Tianyu Fang","submitted_at":"2025-03-12T15:48:35Z","abstract_excerpt":"Integrated sensing and communications (ISAC) has emerged as a promising paradigm to unify wireless communications and radar sensing, enabling efficient spectrum and hardware utilization. A core challenge with realizing the gains of ISAC stems from the unique challenges of dual purpose beamforming design due to the highly non-convex nature of key performance metrics such as sum rate for communications and the Cramer-Rao lower bound (CRLB) for sensing. In this paper, we propose a low-complexity structured approach to ISAC beamforming optimization to simultaneously enhance spectral efficiency and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.09489","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/2503.09489/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":"2503.09489","created_at":"2026-07-05T10:29:57.089645+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.09489v1","created_at":"2026-07-05T10:29:57.089645+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.09489","created_at":"2026-07-05T10:29:57.089645+00:00"},{"alias_kind":"pith_short_12","alias_value":"QMVA3BYVM25U","created_at":"2026-07-05T10:29:57.089645+00:00"},{"alias_kind":"pith_short_16","alias_value":"QMVA3BYVM25UXKLX","created_at":"2026-07-05T10:29:57.089645+00:00"},{"alias_kind":"pith_short_8","alias_value":"QMVA3BYV","created_at":"2026-07-05T10:29:57.089645+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.18166","citing_title":"Cram\\'{e}r-Rao Bound Optimization for Near-Field ISAC with Extended Targets","ref_index":14,"is_internal_anchor":false},{"citing_arxiv_id":"2604.15956","citing_title":"FP-ANeT: A Fixed-Point Attention Network for Hybrid-Field THz Ultra-massive MIMO Channel Estimation","ref_index":12,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR","json":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR.json","graph_json":"https://pith.science/api/pith-number/QMVA3BYVM25UXKLX6DNEX2JUZR/graph.json","events_json":"https://pith.science/api/pith-number/QMVA3BYVM25UXKLX6DNEX2JUZR/events.json","paper":"https://pith.science/paper/QMVA3BYV"},"agent_actions":{"view_html":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR","download_json":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR.json","view_paper":"https://pith.science/paper/QMVA3BYV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.09489&json=true","fetch_graph":"https://pith.science/api/pith-number/QMVA3BYVM25UXKLX6DNEX2JUZR/graph.json","fetch_events":"https://pith.science/api/pith-number/QMVA3BYVM25UXKLX6DNEX2JUZR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR/action/storage_attestation","attest_author":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR/action/author_attestation","sign_citation":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR/action/citation_signature","submit_replication":"https://pith.science/pith/QMVA3BYVM25UXKLX6DNEX2JUZR/action/replication_record"}},"created_at":"2026-07-05T10:29:57.089645+00:00","updated_at":"2026-07-05T10:29:57.089645+00:00"}