{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:PM3FR44WBVUPDC6REVLDPGON3B","short_pith_number":"pith:PM3FR44W","schema_version":"1.0","canonical_sha256":"7b3658f3960d68f18bd125563799cdd8755c514e51e0dde0d7b776fb7ac786c8","source":{"kind":"arxiv","id":"1711.06548","version":2},"attestation_state":"computed","paper":{"title":"FDD Massive MIMO Channel Estimation with Arbitrary 2D-Array Geometry","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"An Liu, Jisheng Dai, Vincent K. N. Lau","submitted_at":"2017-11-12T12:22:02Z","abstract_excerpt":"This paper addresses the problem of downlink channel estimation in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. The existing methods usually exploit hidden sparsity under a discrete Fourier transform (DFT) basis to estimate the cdownlink channel. However, there are at least two shortcomings of these DFT-based methods: 1) they are applicable to uniform linear arrays (ULAs) only, since the DFT basis requires a special structure of ULAs, and 2) they always suffer from a performance loss due to the leakage of energy over some DFT bins. To deal with the "},"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":"1711.06548","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2017-11-12T12:22:02Z","cross_cats_sorted":[],"title_canon_sha256":"2cfa2554b1be67dfe9689aaa5601b2183fcdfd0c0373cab7101c975b32177c53","abstract_canon_sha256":"ff734a8a9b5534ad2b6b91d9f1dbfc7203eafdc2ef45809bae8dbc3d9adda468"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:39.221713Z","signature_b64":"76Q5Dqy1IbIj3fsJEi+cC8d2wKV8ZylcmcodrxdiwtLlbmN8eF0EuHFPdwIJSsjdVdoRiSAM4D2uNP9AP/AMDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b3658f3960d68f18bd125563799cdd8755c514e51e0dde0d7b776fb7ac786c8","last_reissued_at":"2026-05-18T00:22:39.221325Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:39.221325Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FDD Massive MIMO Channel Estimation with Arbitrary 2D-Array Geometry","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"An Liu, Jisheng Dai, Vincent K. N. Lau","submitted_at":"2017-11-12T12:22:02Z","abstract_excerpt":"This paper addresses the problem of downlink channel estimation in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. The existing methods usually exploit hidden sparsity under a discrete Fourier transform (DFT) basis to estimate the cdownlink channel. However, there are at least two shortcomings of these DFT-based methods: 1) they are applicable to uniform linear arrays (ULAs) only, since the DFT basis requires a special structure of ULAs, and 2) they always suffer from a performance loss due to the leakage of energy over some DFT bins. To deal with the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.06548","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":""},"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":"1711.06548","created_at":"2026-05-18T00:22:39.221382+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.06548v2","created_at":"2026-05-18T00:22:39.221382+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.06548","created_at":"2026-05-18T00:22:39.221382+00:00"},{"alias_kind":"pith_short_12","alias_value":"PM3FR44WBVUP","created_at":"2026-05-18T12:31:37.085036+00:00"},{"alias_kind":"pith_short_16","alias_value":"PM3FR44WBVUPDC6R","created_at":"2026-05-18T12:31:37.085036+00:00"},{"alias_kind":"pith_short_8","alias_value":"PM3FR44W","created_at":"2026-05-18T12:31:37.085036+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/PM3FR44WBVUPDC6REVLDPGON3B","json":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B.json","graph_json":"https://pith.science/api/pith-number/PM3FR44WBVUPDC6REVLDPGON3B/graph.json","events_json":"https://pith.science/api/pith-number/PM3FR44WBVUPDC6REVLDPGON3B/events.json","paper":"https://pith.science/paper/PM3FR44W"},"agent_actions":{"view_html":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B","download_json":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B.json","view_paper":"https://pith.science/paper/PM3FR44W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.06548&json=true","fetch_graph":"https://pith.science/api/pith-number/PM3FR44WBVUPDC6REVLDPGON3B/graph.json","fetch_events":"https://pith.science/api/pith-number/PM3FR44WBVUPDC6REVLDPGON3B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B/action/storage_attestation","attest_author":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B/action/author_attestation","sign_citation":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B/action/citation_signature","submit_replication":"https://pith.science/pith/PM3FR44WBVUPDC6REVLDPGON3B/action/replication_record"}},"created_at":"2026-05-18T00:22:39.221382+00:00","updated_at":"2026-05-18T00:22:39.221382+00:00"}