{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:SRAPGSMQXIS3TFMLDZI6FT5YBJ","short_pith_number":"pith:SRAPGSMQ","canonical_record":{"source":{"id":"1907.00766","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-07-01T13:42:12Z","cross_cats_sorted":[],"title_canon_sha256":"08d6130c22a2cee92c8301e2006b79895115946883fa1e37f1b8c407119d54bd","abstract_canon_sha256":"50bea356bd63bd251197dda6e9f519aeff07c69ba08805ac2f4fd83942e6538d"},"schema_version":"1.0"},"canonical_sha256":"9440f34990ba25b9958b1e51e2cfb80a77dcdb1f5e471a7ed0e4602166a1397d","source":{"kind":"arxiv","id":"1907.00766","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.00766","created_at":"2026-05-17T23:41:48Z"},{"alias_kind":"arxiv_version","alias_value":"1907.00766v1","created_at":"2026-05-17T23:41:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.00766","created_at":"2026-05-17T23:41:48Z"},{"alias_kind":"pith_short_12","alias_value":"SRAPGSMQXIS3","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"SRAPGSMQXIS3TFML","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"SRAPGSMQ","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:SRAPGSMQXIS3TFMLDZI6FT5YBJ","target":"record","payload":{"canonical_record":{"source":{"id":"1907.00766","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-07-01T13:42:12Z","cross_cats_sorted":[],"title_canon_sha256":"08d6130c22a2cee92c8301e2006b79895115946883fa1e37f1b8c407119d54bd","abstract_canon_sha256":"50bea356bd63bd251197dda6e9f519aeff07c69ba08805ac2f4fd83942e6538d"},"schema_version":"1.0"},"canonical_sha256":"9440f34990ba25b9958b1e51e2cfb80a77dcdb1f5e471a7ed0e4602166a1397d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:48.182452Z","signature_b64":"PcBPCaxhK6uFUzsqpU9ClrDp/1gUq+IUcO9aKN22EQISpY593YE+kVSMvuQfVA72vhoMptHPnjf9EDb1CEqYBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9440f34990ba25b9958b1e51e2cfb80a77dcdb1f5e471a7ed0e4602166a1397d","last_reissued_at":"2026-05-17T23:41:48.181705Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:48.181705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.00766","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":"2026-05-17T23:41:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AVxfgluEZkqaaLj8L0GyBwdgqhMS3t288Z3w9Pgn3g9+vbu8cSZWJ4j/LMJuTjTUIbUKaEBUQuC/6u+gHF0hAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T11:53:16.694072Z"},"content_sha256":"73b48310b53318e13597bbc6842236bffc66572b2961a24c0531c7ed969b4c05","schema_version":"1.0","event_id":"sha256:73b48310b53318e13597bbc6842236bffc66572b2961a24c0531c7ed969b4c05"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:SRAPGSMQXIS3TFMLDZI6FT5YBJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Design and Implementation of a Neural Network Based Predistorter for Enhanced Mobile Broadband","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Alexios Balatsoukas-Stimming, Chance Tarver, Joseph R. Cavallaro","submitted_at":"2019-07-01T13:42:12Z","abstract_excerpt":"Digital predistortion is the process of correcting for nonlinearities in the analog RF front-end of a wireless transmitter. These nonlinearities contribute to adjacent channel leakage, degrade the error vector magnitude of transmitted signals, and often force the transmitter to reduce its transmission power into a more linear but less power-efficient region of the device. Most predistortion techniques are based on polynomial models with an indirect learning architecture which have been shown to be overly sensitive to noise. In this work, we use neural network based predistortion with a novel n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.00766","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:41:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XcKDheR3OcxqORFXG1H0ZXzw/iE5TCUkHRd7hTct3Uk6JSY11zrzlrxOvtDdP51Xi+8Q7En3g/ERIB1kwsm5BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T11:53:16.694474Z"},"content_sha256":"105d2266b2220ebc48be05f2c2c05f124e6651a0594a406819d0e13cd4223d3d","schema_version":"1.0","event_id":"sha256:105d2266b2220ebc48be05f2c2c05f124e6651a0594a406819d0e13cd4223d3d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ/bundle.json","state_url":"https://pith.science/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ/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":"2026-05-26T11:53:16Z","links":{"resolver":"https://pith.science/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ","bundle":"https://pith.science/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ/bundle.json","state":"https://pith.science/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SRAPGSMQXIS3TFMLDZI6FT5YBJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:SRAPGSMQXIS3TFMLDZI6FT5YBJ","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":"50bea356bd63bd251197dda6e9f519aeff07c69ba08805ac2f4fd83942e6538d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-07-01T13:42:12Z","title_canon_sha256":"08d6130c22a2cee92c8301e2006b79895115946883fa1e37f1b8c407119d54bd"},"schema_version":"1.0","source":{"id":"1907.00766","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.00766","created_at":"2026-05-17T23:41:48Z"},{"alias_kind":"arxiv_version","alias_value":"1907.00766v1","created_at":"2026-05-17T23:41:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.00766","created_at":"2026-05-17T23:41:48Z"},{"alias_kind":"pith_short_12","alias_value":"SRAPGSMQXIS3","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"SRAPGSMQXIS3TFML","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"SRAPGSMQ","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:105d2266b2220ebc48be05f2c2c05f124e6651a0594a406819d0e13cd4223d3d","target":"graph","created_at":"2026-05-17T23:41:48Z","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"},"paper":{"abstract_excerpt":"Digital predistortion is the process of correcting for nonlinearities in the analog RF front-end of a wireless transmitter. These nonlinearities contribute to adjacent channel leakage, degrade the error vector magnitude of transmitted signals, and often force the transmitter to reduce its transmission power into a more linear but less power-efficient region of the device. Most predistortion techniques are based on polynomial models with an indirect learning architecture which have been shown to be overly sensitive to noise. In this work, we use neural network based predistortion with a novel n","authors_text":"Alexios Balatsoukas-Stimming, Chance Tarver, Joseph R. Cavallaro","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-07-01T13:42:12Z","title":"Design and Implementation of a Neural Network Based Predistorter for Enhanced Mobile Broadband"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.00766","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":"sha256:73b48310b53318e13597bbc6842236bffc66572b2961a24c0531c7ed969b4c05","target":"record","created_at":"2026-05-17T23:41:48Z","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":"50bea356bd63bd251197dda6e9f519aeff07c69ba08805ac2f4fd83942e6538d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-07-01T13:42:12Z","title_canon_sha256":"08d6130c22a2cee92c8301e2006b79895115946883fa1e37f1b8c407119d54bd"},"schema_version":"1.0","source":{"id":"1907.00766","kind":"arxiv","version":1}},"canonical_sha256":"9440f34990ba25b9958b1e51e2cfb80a77dcdb1f5e471a7ed0e4602166a1397d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9440f34990ba25b9958b1e51e2cfb80a77dcdb1f5e471a7ed0e4602166a1397d","first_computed_at":"2026-05-17T23:41:48.181705Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:48.181705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PcBPCaxhK6uFUzsqpU9ClrDp/1gUq+IUcO9aKN22EQISpY593YE+kVSMvuQfVA72vhoMptHPnjf9EDb1CEqYBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:48.182452Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.00766","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73b48310b53318e13597bbc6842236bffc66572b2961a24c0531c7ed969b4c05","sha256:105d2266b2220ebc48be05f2c2c05f124e6651a0594a406819d0e13cd4223d3d"],"state_sha256":"85a00abf9c8ca491645b60fb2819d3d1966795b8852226759dd91cfaf856f657"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UJoMxzEsonq5jGFQPcGrAnqepaR/QmN8fwAvEt1eRhZV6UR+56kM297g/wsnz+vGr0nGtbx/XYdnbNvoowTdDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T11:53:16.697161Z","bundle_sha256":"f8c585ca6bd53e5491652c89168a72e1284560aadc05be6b045426cf9e1c00fe"}}