{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:Q6TVEI65F2MNXPDRCVXYX2FXWL","short_pith_number":"pith:Q6TVEI65","canonical_record":{"source":{"id":"2307.04819","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2023-07-10T18:04:26Z","cross_cats_sorted":[],"title_canon_sha256":"e70578789256d6147224b11401338cd726303f4e50575606f789765673e864c5","abstract_canon_sha256":"088230ad95e1cf1c970615b410ba659cbf4463953dc60a99391752f5b5695d34"},"schema_version":"1.0"},"canonical_sha256":"87a75223dd2e98dbbc71156f8be8b7b2ceaba0cddc50159c0469df872b68bb56","source":{"kind":"arxiv","id":"2307.04819","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.04819","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"arxiv_version","alias_value":"2307.04819v2","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.04819","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"pith_short_12","alias_value":"Q6TVEI65F2MN","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"pith_short_16","alias_value":"Q6TVEI65F2MNXPDR","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"pith_short_8","alias_value":"Q6TVEI65","created_at":"2026-07-05T07:16:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:Q6TVEI65F2MNXPDRCVXYX2FXWL","target":"record","payload":{"canonical_record":{"source":{"id":"2307.04819","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2023-07-10T18:04:26Z","cross_cats_sorted":[],"title_canon_sha256":"e70578789256d6147224b11401338cd726303f4e50575606f789765673e864c5","abstract_canon_sha256":"088230ad95e1cf1c970615b410ba659cbf4463953dc60a99391752f5b5695d34"},"schema_version":"1.0"},"canonical_sha256":"87a75223dd2e98dbbc71156f8be8b7b2ceaba0cddc50159c0469df872b68bb56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:16:44.066110Z","signature_b64":"WEC7TiYyOu5GsTziquEjIdbubtkktIaUMsl3/n4WbvJHOO4RxAQkwmB1rVZ6x6e1SQYadfHSUYN19TPlR2nQDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"87a75223dd2e98dbbc71156f8be8b7b2ceaba0cddc50159c0469df872b68bb56","last_reissued_at":"2026-07-05T07:16:44.065552Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:16:44.065552Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.04819","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":"2026-07-05T07:16:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+OKNEfpHKm+DkA11LG1/qXXpJZAmWUzIjwMnifJ2oa3ysfMMil7E9p3zSvlXPvRNozExkHfgILj0BIz324BhCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T02:49:01.015425Z"},"content_sha256":"b591b3eb72071b3e3add12f72431d9ad19d4364e276ee840fbcaf080b07933ca","schema_version":"1.0","event_id":"sha256:b591b3eb72071b3e3add12f72431d9ad19d4364e276ee840fbcaf080b07933ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:Q6TVEI65F2MNXPDRCVXYX2FXWL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Kalman Filter based Low Complexity Throughput Prediction Algorithm for 5G Cellular Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Ayan Chakraborty, Basabdatta Palit, Mayukh Biswas","submitted_at":"2023-07-10T18:04:26Z","abstract_excerpt":"Throughput Prediction is one of the primary preconditions for the uninterrupted operation of several network-aware mobile applications, namely video streaming. Recent works have advocated using Machine Learning (ML) and Deep Learning (DL) for cellular network throughput prediction. In contrast, this work has proposed a low computationally complex simple solution which models the future throughput as a multiple linear regression of several present network parameters and present throughput. It then feeds the variance of prediction error and measurement error, which is inherent in any measurement"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.04819","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/2307.04819/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":"2026-07-05T07:16:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EsHteP0CpSbhKP2wrPvjZ9FzJq39TFPwMLdZKtFXNclvcHlqpJ+1EQXGJThX6GFaYhAr77xl0fEpGDrHDPRTDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T02:49:01.015910Z"},"content_sha256":"2be793d8fa267b614e655ba705601bf8644a6c3eae3ad6052d0c6adf29ffcd13","schema_version":"1.0","event_id":"sha256:2be793d8fa267b614e655ba705601bf8644a6c3eae3ad6052d0c6adf29ffcd13"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL/bundle.json","state_url":"https://pith.science/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL/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":"2026-07-09T02:49:01Z","links":{"resolver":"https://pith.science/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL","bundle":"https://pith.science/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL/bundle.json","state":"https://pith.science/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q6TVEI65F2MNXPDRCVXYX2FXWL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:Q6TVEI65F2MNXPDRCVXYX2FXWL","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":"088230ad95e1cf1c970615b410ba659cbf4463953dc60a99391752f5b5695d34","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2023-07-10T18:04:26Z","title_canon_sha256":"e70578789256d6147224b11401338cd726303f4e50575606f789765673e864c5"},"schema_version":"1.0","source":{"id":"2307.04819","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.04819","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"arxiv_version","alias_value":"2307.04819v2","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.04819","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"pith_short_12","alias_value":"Q6TVEI65F2MN","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"pith_short_16","alias_value":"Q6TVEI65F2MNXPDR","created_at":"2026-07-05T07:16:44Z"},{"alias_kind":"pith_short_8","alias_value":"Q6TVEI65","created_at":"2026-07-05T07:16:44Z"}],"graph_snapshots":[{"event_id":"sha256:2be793d8fa267b614e655ba705601bf8644a6c3eae3ad6052d0c6adf29ffcd13","target":"graph","created_at":"2026-07-05T07:16:44Z","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/2307.04819/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Throughput Prediction is one of the primary preconditions for the uninterrupted operation of several network-aware mobile applications, namely video streaming. Recent works have advocated using Machine Learning (ML) and Deep Learning (DL) for cellular network throughput prediction. In contrast, this work has proposed a low computationally complex simple solution which models the future throughput as a multiple linear regression of several present network parameters and present throughput. It then feeds the variance of prediction error and measurement error, which is inherent in any measurement","authors_text":"Ayan Chakraborty, Basabdatta Palit, Mayukh Biswas","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2023-07-10T18:04:26Z","title":"A Kalman Filter based Low Complexity Throughput Prediction Algorithm for 5G Cellular Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.04819","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:b591b3eb72071b3e3add12f72431d9ad19d4364e276ee840fbcaf080b07933ca","target":"record","created_at":"2026-07-05T07:16:44Z","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":"088230ad95e1cf1c970615b410ba659cbf4463953dc60a99391752f5b5695d34","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2023-07-10T18:04:26Z","title_canon_sha256":"e70578789256d6147224b11401338cd726303f4e50575606f789765673e864c5"},"schema_version":"1.0","source":{"id":"2307.04819","kind":"arxiv","version":2}},"canonical_sha256":"87a75223dd2e98dbbc71156f8be8b7b2ceaba0cddc50159c0469df872b68bb56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"87a75223dd2e98dbbc71156f8be8b7b2ceaba0cddc50159c0469df872b68bb56","first_computed_at":"2026-07-05T07:16:44.065552Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:16:44.065552Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WEC7TiYyOu5GsTziquEjIdbubtkktIaUMsl3/n4WbvJHOO4RxAQkwmB1rVZ6x6e1SQYadfHSUYN19TPlR2nQDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:16:44.066110Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.04819","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b591b3eb72071b3e3add12f72431d9ad19d4364e276ee840fbcaf080b07933ca","sha256:2be793d8fa267b614e655ba705601bf8644a6c3eae3ad6052d0c6adf29ffcd13"],"state_sha256":"10adb48e947ed686ec3eba5a1d12f445997e1878f397cff1da92de3897ecd442"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8YVzabG+kT4kxH0fyFkRbDvQIRB286YKKD3SYsGRujUFGue4jmnKsXMOgCRDh3DuI2C6xwYvPFxeYXZ05ez2AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T02:49:01.017953Z","bundle_sha256":"c95ec82106e93fdd8b4384fcd63b53b8e285e85c5521444802c1e311f6a6243c"}}