{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:I7GV6LWAL3723S7HLBI77VJ3NL","short_pith_number":"pith:I7GV6LWA","canonical_record":{"source":{"id":"2104.13656","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-04-28T09:24:34Z","cross_cats_sorted":[],"title_canon_sha256":"9ed63870ece73ab778cbea43198e3acd598bb58bf7c45bd3faa98b7f693ac516","abstract_canon_sha256":"32a787ebb6bd9946f73d897215ed166be9e06a4d0b3619f72a903a782184a3a6"},"schema_version":"1.0"},"canonical_sha256":"47cd5f2ec05effadcbe75851ffd53b6af77d1be516b16b9cad06ff0ba5b08118","source":{"kind":"arxiv","id":"2104.13656","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.13656","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"arxiv_version","alias_value":"2104.13656v2","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.13656","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"pith_short_12","alias_value":"I7GV6LWAL372","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"pith_short_16","alias_value":"I7GV6LWAL3723S7H","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"pith_short_8","alias_value":"I7GV6LWA","created_at":"2026-07-05T03:15:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:I7GV6LWAL3723S7HLBI77VJ3NL","target":"record","payload":{"canonical_record":{"source":{"id":"2104.13656","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-04-28T09:24:34Z","cross_cats_sorted":[],"title_canon_sha256":"9ed63870ece73ab778cbea43198e3acd598bb58bf7c45bd3faa98b7f693ac516","abstract_canon_sha256":"32a787ebb6bd9946f73d897215ed166be9e06a4d0b3619f72a903a782184a3a6"},"schema_version":"1.0"},"canonical_sha256":"47cd5f2ec05effadcbe75851ffd53b6af77d1be516b16b9cad06ff0ba5b08118","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:15:33.849402Z","signature_b64":"5LdegVAev3g9vi6kbCHt+Ycgl5SDehBPPxBwF5/xn2hwxmVI3xkdbrzP2y2PWIqDHUBnnMYG+irtlUbruuqDDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47cd5f2ec05effadcbe75851ffd53b6af77d1be516b16b9cad06ff0ba5b08118","last_reissued_at":"2026-07-05T03:15:33.848866Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:15:33.848866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.13656","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:15:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KU0UV6VFqxmjDm9C1ONeNCg3AMSbefJA28upz67vjcjeP66gpFu2Wd3xrP3JV1z7OcfYIUf8IPF6zIPvzTGnCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T11:31:36.595761Z"},"content_sha256":"d45eac384d1cd803c6cde94a79a3ddb7b88b42c4b2c30d8baf42aa814e5a395c","schema_version":"1.0","event_id":"sha256:d45eac384d1cd803c6cde94a79a3ddb7b88b42c4b2c30d8baf42aa814e5a395c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:I7GV6LWAL3723S7HLBI77VJ3NL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Channel Estimation Based on Model-Driven Deep Learning for Wideband mmWave Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Chao-Kai Wen, Geoffrey Ye Li, Hengtao He, Shi Jin, Weijie Jin","submitted_at":"2021-04-28T09:24:34Z","abstract_excerpt":"Channel estimation in wideband millimeter-wave (mmWave) systems is very challenging due to the beam squint effect. To solve the problem, we propose a learnable iterative shrinkage thresholding algorithm-based channel estimator (LISTA-CE) based on deep learning. The proposed channel estimator can learn to transform the beam-frequency mmWave channel into the domain with sparse features through training data. The transform domain enables us to adopt a simple denoiser with few trainable parameters. We further enhance the adaptivity of the estimator by introducing hypernetwork to automatically gene"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.13656","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/2104.13656/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:15:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0XlU8ddSupCGlVTLC1JX+m7hlzPUbLEDyHyBFu1HvX+QY94BxIrRpjvdeYevqk3qJhx5ZOqmR5aKfCiO+i/0Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T11:31:36.596308Z"},"content_sha256":"48a01c44813f7c22970ace9a330dce3e7a0a05775da3a80f6c466561ce9f25f7","schema_version":"1.0","event_id":"sha256:48a01c44813f7c22970ace9a330dce3e7a0a05775da3a80f6c466561ce9f25f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I7GV6LWAL3723S7HLBI77VJ3NL/bundle.json","state_url":"https://pith.science/pith/I7GV6LWAL3723S7HLBI77VJ3NL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I7GV6LWAL3723S7HLBI77VJ3NL/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-15T11:31:36Z","links":{"resolver":"https://pith.science/pith/I7GV6LWAL3723S7HLBI77VJ3NL","bundle":"https://pith.science/pith/I7GV6LWAL3723S7HLBI77VJ3NL/bundle.json","state":"https://pith.science/pith/I7GV6LWAL3723S7HLBI77VJ3NL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I7GV6LWAL3723S7HLBI77VJ3NL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:I7GV6LWAL3723S7HLBI77VJ3NL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"32a787ebb6bd9946f73d897215ed166be9e06a4d0b3619f72a903a782184a3a6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-04-28T09:24:34Z","title_canon_sha256":"9ed63870ece73ab778cbea43198e3acd598bb58bf7c45bd3faa98b7f693ac516"},"schema_version":"1.0","source":{"id":"2104.13656","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.13656","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"arxiv_version","alias_value":"2104.13656v2","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.13656","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"pith_short_12","alias_value":"I7GV6LWAL372","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"pith_short_16","alias_value":"I7GV6LWAL3723S7H","created_at":"2026-07-05T03:15:33Z"},{"alias_kind":"pith_short_8","alias_value":"I7GV6LWA","created_at":"2026-07-05T03:15:33Z"}],"graph_snapshots":[{"event_id":"sha256:48a01c44813f7c22970ace9a330dce3e7a0a05775da3a80f6c466561ce9f25f7","target":"graph","created_at":"2026-07-05T03:15:33Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2104.13656/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Channel estimation in wideband millimeter-wave (mmWave) systems is very challenging due to the beam squint effect. To solve the problem, we propose a learnable iterative shrinkage thresholding algorithm-based channel estimator (LISTA-CE) based on deep learning. The proposed channel estimator can learn to transform the beam-frequency mmWave channel into the domain with sparse features through training data. The transform domain enables us to adopt a simple denoiser with few trainable parameters. We further enhance the adaptivity of the estimator by introducing hypernetwork to automatically gene","authors_text":"Chao-Kai Wen, Geoffrey Ye Li, Hengtao He, Shi Jin, Weijie Jin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-04-28T09:24:34Z","title":"Adaptive Channel Estimation Based on Model-Driven Deep Learning for Wideband mmWave Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.13656","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d45eac384d1cd803c6cde94a79a3ddb7b88b42c4b2c30d8baf42aa814e5a395c","target":"record","created_at":"2026-07-05T03:15:33Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"32a787ebb6bd9946f73d897215ed166be9e06a4d0b3619f72a903a782184a3a6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-04-28T09:24:34Z","title_canon_sha256":"9ed63870ece73ab778cbea43198e3acd598bb58bf7c45bd3faa98b7f693ac516"},"schema_version":"1.0","source":{"id":"2104.13656","kind":"arxiv","version":2}},"canonical_sha256":"47cd5f2ec05effadcbe75851ffd53b6af77d1be516b16b9cad06ff0ba5b08118","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"47cd5f2ec05effadcbe75851ffd53b6af77d1be516b16b9cad06ff0ba5b08118","first_computed_at":"2026-07-05T03:15:33.848866Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:15:33.848866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5LdegVAev3g9vi6kbCHt+Ycgl5SDehBPPxBwF5/xn2hwxmVI3xkdbrzP2y2PWIqDHUBnnMYG+irtlUbruuqDDg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:15:33.849402Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.13656","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d45eac384d1cd803c6cde94a79a3ddb7b88b42c4b2c30d8baf42aa814e5a395c","sha256:48a01c44813f7c22970ace9a330dce3e7a0a05775da3a80f6c466561ce9f25f7"],"state_sha256":"079bd22eac1c6734ce14928c4270d76b04417200f4af55895202ccbc53ba333d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0119ksebiNSKTswg+9AgyvyGpT2geyVE90ieiCMMO1/moydp/2oDCjXqDbkqMEIcYXn3jYyzJTFZSJYOU4AWCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T11:31:36.602823Z","bundle_sha256":"fcc8f9c8592c95b2dff8f47e6da772d2cb284ab8d01b96638ef32603abb03ac2"}}