{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4PYF3WF4UQM5UPWTOQJ7BMPKUX","short_pith_number":"pith:4PYF3WF4","canonical_record":{"source":{"id":"1906.06007","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-14T03:51:20Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"614f1d8de7fbe08d6908d2d1fd6fe6159b04f8d321e8ba8d90121786df5a9600","abstract_canon_sha256":"e4a0a3dd748207401d4e4755057edce882cc94b5e4570c50f7d5514a6015134f"},"schema_version":"1.0"},"canonical_sha256":"e3f05dd8bca419da3ed37413f0b1eaa5d1282fe2a397cdd98e651b2170560921","source":{"kind":"arxiv","id":"1906.06007","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.06007","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"arxiv_version","alias_value":"1906.06007v1","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.06007","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"pith_short_12","alias_value":"4PYF3WF4UQM5","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"pith_short_16","alias_value":"4PYF3WF4UQM5UPWT","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"pith_short_8","alias_value":"4PYF3WF4","created_at":"2026-07-05T09:27:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4PYF3WF4UQM5UPWTOQJ7BMPKUX","target":"record","payload":{"canonical_record":{"source":{"id":"1906.06007","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-14T03:51:20Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"614f1d8de7fbe08d6908d2d1fd6fe6159b04f8d321e8ba8d90121786df5a9600","abstract_canon_sha256":"e4a0a3dd748207401d4e4755057edce882cc94b5e4570c50f7d5514a6015134f"},"schema_version":"1.0"},"canonical_sha256":"e3f05dd8bca419da3ed37413f0b1eaa5d1282fe2a397cdd98e651b2170560921","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:27:44.209852Z","signature_b64":"y+ALIU/5uvmA6e3dnHnoxqkG/x2+pwXOjeJ8ZdHhM39slYjVhe/OLfXZlz+bjuwI1MAnQymGSaEILwNQeBZhAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3f05dd8bca419da3ed37413f0b1eaa5d1282fe2a397cdd98e651b2170560921","last_reissued_at":"2026-07-05T09:27:44.209431Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:27:44.209431Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.06007","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:27:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NsaUoB1RGX5YiowMbEUTansUECLJpLjBCqgQzkHlcwGdfwQo9SvhZpLl5OSS7bkqxU4fTfqY0IIZa8G9ToQlDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T12:31:16.656753Z"},"content_sha256":"08c37ff8e907db7d2f091882226e005f89de6f1db8e1542914642eeeb0235b72","schema_version":"1.0","event_id":"sha256:08c37ff8e907db7d2f091882226e005f89de6f1db8e1542914642eeeb0235b72"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4PYF3WF4UQM5UPWTOQJ7BMPKUX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"eess.SP","authors_text":"Chao-Kai Wen, Geoffrey Ye Li, Jiajia Guo, Shi Jin","submitted_at":"2019-06-14T03:51:20Z","abstract_excerpt":"Massive multiple-input multiple-output (MIMO) is a promising technology to increase link capacity and energy efficiency. However, these benefits are based on available channel state information (CSI) at the base station (BS). Therefore, user equipment (UE) needs to keep on feeding CSI back to the BS, thereby consuming precious bandwidth resource. Large-scale antennas at the BS for massive MIMO seriously increase this overhead. In this paper, we propose a multiple-rate compressive sensing neural network framework to compress and quantize the CSI. This framework not only improves reconstruction "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.06007","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/1906.06007/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":"2026-07-05T09:27:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CTf1d5CGA1vE0VqCAaOCNodljddDVEz+In7vpsdJUTH8VBR2DTcPQr9JIXTm1gxhoyDigwd6NU1G5EsK3/8VAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T12:31:16.657290Z"},"content_sha256":"11ba304977fb82d92e95af8e7867f9c35e7154bcd06332f4cb2dc9ac2420970e","schema_version":"1.0","event_id":"sha256:11ba304977fb82d92e95af8e7867f9c35e7154bcd06332f4cb2dc9ac2420970e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX/bundle.json","state_url":"https://pith.science/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX/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":"2026-08-16T12:31:16Z","links":{"resolver":"https://pith.science/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX","bundle":"https://pith.science/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX/bundle.json","state":"https://pith.science/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4PYF3WF4UQM5UPWTOQJ7BMPKUX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4PYF3WF4UQM5UPWTOQJ7BMPKUX","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":"e4a0a3dd748207401d4e4755057edce882cc94b5e4570c50f7d5514a6015134f","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-14T03:51:20Z","title_canon_sha256":"614f1d8de7fbe08d6908d2d1fd6fe6159b04f8d321e8ba8d90121786df5a9600"},"schema_version":"1.0","source":{"id":"1906.06007","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.06007","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"arxiv_version","alias_value":"1906.06007v1","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.06007","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"pith_short_12","alias_value":"4PYF3WF4UQM5","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"pith_short_16","alias_value":"4PYF3WF4UQM5UPWT","created_at":"2026-07-05T09:27:44Z"},{"alias_kind":"pith_short_8","alias_value":"4PYF3WF4","created_at":"2026-07-05T09:27:44Z"}],"graph_snapshots":[{"event_id":"sha256:11ba304977fb82d92e95af8e7867f9c35e7154bcd06332f4cb2dc9ac2420970e","target":"graph","created_at":"2026-07-05T09:27:44Z","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/1906.06007/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Massive multiple-input multiple-output (MIMO) is a promising technology to increase link capacity and energy efficiency. However, these benefits are based on available channel state information (CSI) at the base station (BS). Therefore, user equipment (UE) needs to keep on feeding CSI back to the BS, thereby consuming precious bandwidth resource. Large-scale antennas at the BS for massive MIMO seriously increase this overhead. In this paper, we propose a multiple-rate compressive sensing neural network framework to compress and quantize the CSI. This framework not only improves reconstruction ","authors_text":"Chao-Kai Wen, Geoffrey Ye Li, Jiajia Guo, Shi Jin","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-14T03:51:20Z","title":"Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.06007","kind":"arxiv","version":1},"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":"sha256:08c37ff8e907db7d2f091882226e005f89de6f1db8e1542914642eeeb0235b72","target":"record","created_at":"2026-07-05T09:27:44Z","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":"e4a0a3dd748207401d4e4755057edce882cc94b5e4570c50f7d5514a6015134f","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-14T03:51:20Z","title_canon_sha256":"614f1d8de7fbe08d6908d2d1fd6fe6159b04f8d321e8ba8d90121786df5a9600"},"schema_version":"1.0","source":{"id":"1906.06007","kind":"arxiv","version":1}},"canonical_sha256":"e3f05dd8bca419da3ed37413f0b1eaa5d1282fe2a397cdd98e651b2170560921","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3f05dd8bca419da3ed37413f0b1eaa5d1282fe2a397cdd98e651b2170560921","first_computed_at":"2026-07-05T09:27:44.209431Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:27:44.209431Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y+ALIU/5uvmA6e3dnHnoxqkG/x2+pwXOjeJ8ZdHhM39slYjVhe/OLfXZlz+bjuwI1MAnQymGSaEILwNQeBZhAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:27:44.209852Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.06007","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:08c37ff8e907db7d2f091882226e005f89de6f1db8e1542914642eeeb0235b72","sha256:11ba304977fb82d92e95af8e7867f9c35e7154bcd06332f4cb2dc9ac2420970e"],"state_sha256":"e2c9d39dd221f2bfe9446daab16c945bf26540793293aa2eb6fc2059fa1c3ccb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LAsxjG8/VddY7TLG/ZwEvXuSXNa/LCS/nvnn6htexCzT1ismigIxbTCqfsrBwT14NehxWVXj6uTM5MCfwTs3AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T12:31:16.660620Z","bundle_sha256":"e336d06889bbeca3e27cfd2b4c7ce342c309140009aaf3c772ff74a5da172879"}}