{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:YCJOK5EZBRKYQJJMTMK4TNBVU3","short_pith_number":"pith:YCJOK5EZ","schema_version":"1.0","canonical_sha256":"c092e574990c5588252c9b15c9b435a6d02c41075b93639d28ba4755cb14ae06","source":{"kind":"arxiv","id":"1804.11204","version":1},"attestation_state":"computed","paper":{"title":"Spatial Covariance Estimation for Millimeter Wave Hybrid Systems using Out-of-Band Information","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Anum Ali, Nuria Gonz\\'alez-Prelcic, Robert W. Heath Jr","submitted_at":"2018-04-26T18:31:35Z","abstract_excerpt":"In high mobility applications of millimeter wave (mmWave) communications, e.g., vehicle-to-everything communication and next-generation cellular communication, frequent link configuration can be a source of significant overhead. We use the sub-6 GHz channel covariance as an out-of-band side information for mmWave link configuration. Assuming: (i) a fully digital architecture at sub-6 GHz; and (ii) a hybrid analog-digital architecture at mmWave, we propose an out-of-band covariance translation approach and an out-of-band aided compressed covariance estimation approach. For covariance translatio"},"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":"1804.11204","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2018-04-26T18:31:35Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"a80ad25436978a486e3e92d176715b3fa2b7ff095420711cb7e9eaf5426fa060","abstract_canon_sha256":"d37e16a560490299c8d79d53b3211962a1230c26fca81208e1f56351e0455b1b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:17:14.284217Z","signature_b64":"g+AUjWnKfWnCg+MthzxTVsAps4hbDCYMMJAK3oRCLp368jWP/8ZGCWj8GvYoJ1OImoZp4C3IpAYuHN6GtuY3DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c092e574990c5588252c9b15c9b435a6d02c41075b93639d28ba4755cb14ae06","last_reissued_at":"2026-05-18T00:17:14.283707Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:17:14.283707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Spatial Covariance Estimation for Millimeter Wave Hybrid Systems using Out-of-Band Information","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Anum Ali, Nuria Gonz\\'alez-Prelcic, Robert W. Heath Jr","submitted_at":"2018-04-26T18:31:35Z","abstract_excerpt":"In high mobility applications of millimeter wave (mmWave) communications, e.g., vehicle-to-everything communication and next-generation cellular communication, frequent link configuration can be a source of significant overhead. We use the sub-6 GHz channel covariance as an out-of-band side information for mmWave link configuration. Assuming: (i) a fully digital architecture at sub-6 GHz; and (ii) a hybrid analog-digital architecture at mmWave, we propose an out-of-band covariance translation approach and an out-of-band aided compressed covariance estimation approach. For covariance translatio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.11204","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":"1804.11204","created_at":"2026-05-18T00:17:14.283791+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.11204v1","created_at":"2026-05-18T00:17:14.283791+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.11204","created_at":"2026-05-18T00:17:14.283791+00:00"},{"alias_kind":"pith_short_12","alias_value":"YCJOK5EZBRKY","created_at":"2026-05-18T12:33:04.347982+00:00"},{"alias_kind":"pith_short_16","alias_value":"YCJOK5EZBRKYQJJM","created_at":"2026-05-18T12:33:04.347982+00:00"},{"alias_kind":"pith_short_8","alias_value":"YCJOK5EZ","created_at":"2026-05-18T12:33:04.347982+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"1907.04423","citing_title":"Off-Grid Aware Channel and Covariance Estimation in mmWave Networks","ref_index":19,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3","json":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3.json","graph_json":"https://pith.science/api/pith-number/YCJOK5EZBRKYQJJMTMK4TNBVU3/graph.json","events_json":"https://pith.science/api/pith-number/YCJOK5EZBRKYQJJMTMK4TNBVU3/events.json","paper":"https://pith.science/paper/YCJOK5EZ"},"agent_actions":{"view_html":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3","download_json":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3.json","view_paper":"https://pith.science/paper/YCJOK5EZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.11204&json=true","fetch_graph":"https://pith.science/api/pith-number/YCJOK5EZBRKYQJJMTMK4TNBVU3/graph.json","fetch_events":"https://pith.science/api/pith-number/YCJOK5EZBRKYQJJMTMK4TNBVU3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3/action/storage_attestation","attest_author":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3/action/author_attestation","sign_citation":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3/action/citation_signature","submit_replication":"https://pith.science/pith/YCJOK5EZBRKYQJJMTMK4TNBVU3/action/replication_record"}},"created_at":"2026-05-18T00:17:14.283791+00:00","updated_at":"2026-05-18T00:17:14.283791+00:00"}