# Strategic Demand-Planning in Wireless Networks: Can Generative-AI Save Spectrum and Energy?

arXiv: https://arxiv.org/abs/2407.02292 · HTML: https://mlsanity.com/paper/2407.02292/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 20 references that are in the map.
- First posted on arXiv 2 Jul 2024.

## Builds on (most cited first, 9 of 9)

- [Large Generative AI Models for Telecom: The Next Big Thing?](https://mlsanity.com/paper/2306.10249/) (2023)
- [Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler](https://mlsanity.com/paper/2311.17451/) (2023)
- [Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study](https://mlsanity.com/paper/2303.17114/) (2023)
- [Generative AI for Semantic Communication: Architecture, Challenges, and Outlook](https://mlsanity.com/paper/2308.15483/) (2023)
- [Generative AI for Physical Layer Communications: A Survey](https://mlsanity.com/paper/2312.05594/) (2023)
- [AI-enabled Future Wireless Networks: Challenges, Opportunities and Open Issues](https://mlsanity.com/paper/2103.04536/) (2021)
- [Integrating Terrestrial and Non-terrestrial Networks: 3D Opportunities and Challenges](https://mlsanity.com/paper/2207.10385/) (2022)
- [Enhancing Next-Generation Urban Connectivity: Is the Integrated HAPS-Terrestrial Network a Solution?](https://mlsanity.com/paper/2307.08202/) (2023)
- [Cell Switching in HAPS-Aided Networking: How the Obscurity of Traffic Loads Affects the Decision](https://mlsanity.com/paper/2405.00387/) (2024)

## Abstract (arXiv)

Generative-AI (GenAI), a novel technology capable of producing various types of outputs, including text, images, and videos, offers significant potential for wireless communications. This article introduces the concept of strategic demand-planning through demand-labeling, demand-shaping, and demand-rescheduling. Accordingly, GenAI is proposed as a powerful tool to facilitate demand-shaping in wireless networks. More specifically, GenAI is used to compress and convert the content of various types (e.g., from a higher bandwidth mode to a lower one, such as from a video to text), which subsequently enhances performance of wireless networks in various usage scenarios, such as cell-switching, user association and load balancing, interference management, as well as disasters and unusual gatherings. Therefore, GenAI can serve a function in saving energy and spectrum in wireless networks. With recent advancements in AI, including sophisticated algorithms like large language models and the development of more powerful hardware built exclusively for AI tasks, such as AI accelerators, the concept of demand-planning, particularly demand-shaping through GenAI, becomes increasingly relevant. Furthermore, recent efforts to make GenAI accessible on devices, such as user terminals, make the implementation of this concept even more straightforward and feasible.