{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:4IK25OXV56FMLZ2HEJYZQ7BAUV","short_pith_number":"pith:4IK25OXV","schema_version":"1.0","canonical_sha256":"e215aebaf5ef8ac5e7472271987c20a5485452169a4dcbd44623cb708dadbcff","source":{"kind":"arxiv","id":"2310.11044","version":3},"attestation_state":"computed","paper":{"title":"A Tutorial on Near-Field XL-MIMO Communications Towards 6G","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Changsheng You, Cheng-Xiang Wang, Haiquan Lu, Jiayi Zhang, Rui Zhang, Shi Jin, Tao Jiang, Xiaohu You, Yong Zeng, Yu Han, Zhenjun Dong, Zhe Wang","submitted_at":"2023-10-17T07:25:00Z","abstract_excerpt":"Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising technology for the sixth-generation (6G) mobile communication networks. By significantly boosting the antenna number or size to at least an order of magnitude beyond current massive MIMO systems, XL-MIMO is expected to unprecedentedly enhance the spectral efficiency and spatial resolution for wireless communication. The evolution from massive MIMO to XL-MIMO is not simply an increase in the array size, but faces new design challenges, in terms of near-field channel modelling, performance analysis, channel estimation,"},"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":"2310.11044","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2023-10-17T07:25:00Z","cross_cats_sorted":["eess.SP","math.IT"],"title_canon_sha256":"d1c8a3ac3c1a43497fe7cd9a296f51ec8c4a43c66d3a1e0b63cb66f6159e4441","abstract_canon_sha256":"8a996eac63c397a240ec30dccc59ac684a1783ee5d03c4c35c651e6132c44306"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:03:44.977265Z","signature_b64":"CS0QfWaDD2AgnkodhfZcWvSF9aDOiT3QY0BvzKKkXgRKGSodMqJU90xnC0Peq5KcJsNNwd4xOXRpDwNVZxfLBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e215aebaf5ef8ac5e7472271987c20a5485452169a4dcbd44623cb708dadbcff","last_reissued_at":"2026-07-05T08:03:44.975976Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:03:44.975976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Tutorial on Near-Field XL-MIMO Communications Towards 6G","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Changsheng You, Cheng-Xiang Wang, Haiquan Lu, Jiayi Zhang, Rui Zhang, Shi Jin, Tao Jiang, Xiaohu You, Yong Zeng, Yu Han, Zhenjun Dong, Zhe Wang","submitted_at":"2023-10-17T07:25:00Z","abstract_excerpt":"Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising technology for the sixth-generation (6G) mobile communication networks. By significantly boosting the antenna number or size to at least an order of magnitude beyond current massive MIMO systems, XL-MIMO is expected to unprecedentedly enhance the spectral efficiency and spatial resolution for wireless communication. The evolution from massive MIMO to XL-MIMO is not simply an increase in the array size, but faces new design challenges, in terms of near-field channel modelling, performance analysis, channel estimation,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.11044","kind":"arxiv","version":3},"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/2310.11044/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":"2310.11044","created_at":"2026-07-05T08:03:44.976073+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.11044v3","created_at":"2026-07-05T08:03:44.976073+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.11044","created_at":"2026-07-05T08:03:44.976073+00:00"},{"alias_kind":"pith_short_12","alias_value":"4IK25OXV56FM","created_at":"2026-07-05T08:03:44.976073+00:00"},{"alias_kind":"pith_short_16","alias_value":"4IK25OXV56FMLZ2H","created_at":"2026-07-05T08:03:44.976073+00:00"},{"alias_kind":"pith_short_8","alias_value":"4IK25OXV","created_at":"2026-07-05T08:03:44.976073+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.23495","citing_title":"Far-Field vs. Near-Field Propagation Channels: Key Differences and Impact on 6G XL-MIMO Performance Evaluation","ref_index":18,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV","json":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV.json","graph_json":"https://pith.science/api/pith-number/4IK25OXV56FMLZ2HEJYZQ7BAUV/graph.json","events_json":"https://pith.science/api/pith-number/4IK25OXV56FMLZ2HEJYZQ7BAUV/events.json","paper":"https://pith.science/paper/4IK25OXV"},"agent_actions":{"view_html":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV","download_json":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV.json","view_paper":"https://pith.science/paper/4IK25OXV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.11044&json=true","fetch_graph":"https://pith.science/api/pith-number/4IK25OXV56FMLZ2HEJYZQ7BAUV/graph.json","fetch_events":"https://pith.science/api/pith-number/4IK25OXV56FMLZ2HEJYZQ7BAUV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV/action/storage_attestation","attest_author":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV/action/author_attestation","sign_citation":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV/action/citation_signature","submit_replication":"https://pith.science/pith/4IK25OXV56FMLZ2HEJYZQ7BAUV/action/replication_record"}},"created_at":"2026-07-05T08:03:44.976073+00:00","updated_at":"2026-07-05T08:03:44.976073+00:00"}