Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation

Xiaowen Xu; Xiaosi Liu; Zhidan Liu; Zhenjiang Li; Kaishun Wu

doi:10.1145/3680207.3765675

Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation

Xiaowen Xu
, Xiaosi Liu
, Zhidan Liu^*
, Zhenjiang Li
, Kaishun Wu

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Accurate modeling of traffic demand through cellular traffic generation is crucial for optimizing base station deployment. We thus present STOUTER, a Spatio-Temporal diffusiOn model for cellUlar Traffic genERation. To effectively capture spatial and temporal dynamics, we pretrain both a temporal graph and a base-station graph, and introduce a Spatio-Temporal Feature Fusion Module (STFFM). On five datasets from two regions, STOUTER reduces Jensen–Shannon Divergence by 52.8% over prior methods, generating distributions that closely match real traffic and aiding downstream planning tasks. © 2025 the owner/author(s).

Original language	English
Title of host publication	ACM MobiCom '25 - Proceedings of the 2025 the 31st Annual International Conference on Mobile Computing and Networking
Place of Publication	New York, NY
Publisher	Association for Computing Machinery
Pages	1326-1328
Number of pages	3
ISBN (Print)	9798400711299
DOIs	https://doi.org/10.1145/3680207.3765675
Publication status	Published - Nov 2025
Event	31st Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2025) - , Hong Kong, China Duration: 4 Nov 2025 → 8 Nov 2025 https://www.sigmobile.org/mobicom/2025/index.html

Publication series

Name	ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking

Conference

Conference	31st Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2025)
Abbreviated title	ACM MobiCom ’25
Place	Hong Kong, China
Period	4/11/25 → 8/11/25
Internet address	https://www.sigmobile.org/mobicom/2025/index.html

Funding

This work was supported in part by National Natural Science Foundations of China under Grant 62172284 and the Guangdong Provincial Key Lab of Integrated Communication, Sensing and Computation for Ubiquitous Internet of Things under Grant 2023B1212010007.

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10.1145/3680207.3765675

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Xu, X., Liu, X., Liu, Z., Li, Z., & Wu, K. (2025). Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation. In ACM MobiCom '25 - Proceedings of the 2025 the 31st Annual International Conference on Mobile Computing and Networking (pp. 1326-1328). (ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking). Association for Computing Machinery. https://doi.org/10.1145/3680207.3765675

Xu, Xiaowen ; Liu, Xiaosi ; Liu, Zhidan et al. / Poster : Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation. ACM MobiCom '25 - Proceedings of the 2025 the 31st Annual International Conference on Mobile Computing and Networking. New York, NY : Association for Computing Machinery, 2025. pp. 1326-1328 (ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking).

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title = "Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation",

abstract = "Accurate modeling of traffic demand through cellular traffic generation is crucial for optimizing base station deployment. We thus present STOUTER, a Spatio-Temporal diffusiOn model for cellUlar Traffic genERation. To effectively capture spatial and temporal dynamics, we pretrain both a temporal graph and a base-station graph, and introduce a Spatio-Temporal Feature Fusion Module (STFFM). On five datasets from two regions, STOUTER reduces Jensen–Shannon Divergence by 52.8\% over prior methods, generating distributions that closely match real traffic and aiding downstream planning tasks. {\textcopyright} 2025 the owner/author(s).",

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series = "ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking",

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note = "31st Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2025), ACM MobiCom {\textquoteright}25 ; Conference date: 04-11-2025 Through 08-11-2025",

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Xu, X, Liu, X, Liu, Z, Li, Z & Wu, K 2025, Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation. in ACM MobiCom '25 - Proceedings of the 2025 the 31st Annual International Conference on Mobile Computing and Networking. ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking, Association for Computing Machinery, New York, NY, pp. 1326-1328, 31st Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2025), Hong Kong, China, 4/11/25. https://doi.org/10.1145/3680207.3765675

Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation. / Xu, Xiaowen; Liu, Xiaosi; Liu, Zhidan et al.
ACM MobiCom '25 - Proceedings of the 2025 the 31st Annual International Conference on Mobile Computing and Networking. New York, NY: Association for Computing Machinery, 2025. p. 1326-1328 (ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Xu, Xiaowen

AU - Liu, Xiaosi

AU - Liu, Zhidan

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AU - Wu, Kaishun

PY - 2025/11

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AB - Accurate modeling of traffic demand through cellular traffic generation is crucial for optimizing base station deployment. We thus present STOUTER, a Spatio-Temporal diffusiOn model for cellUlar Traffic genERation. To effectively capture spatial and temporal dynamics, we pretrain both a temporal graph and a base-station graph, and introduce a Spatio-Temporal Feature Fusion Module (STFFM). On five datasets from two regions, STOUTER reduces Jensen–Shannon Divergence by 52.8% over prior methods, generating distributions that closely match real traffic and aiding downstream planning tasks. © 2025 the owner/author(s).

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M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9798400711299

T3 - ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking

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EP - 1328

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Xu X, Liu X, Liu Z, Li Z, Wu K. Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation. In ACM MobiCom '25 - Proceedings of the 2025 the 31st Annual International Conference on Mobile Computing and Networking. New York, NY: Association for Computing Machinery. 2025. p. 1326-1328. (ACM MobiCom - Proceedings of the Annual International Conference on Mobile Computing and Networking). Epub 2025 Nov 21. doi: 10.1145/3680207.3765675

Poster: Diffusion-Driven Spatio-Temporal Modeling of Cellular Traffic Generation

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