Abstract
From AI-assisted art creation to large language model (LLM)-powered ChatGPT, AI-generated contents and services are becoming a transforming force. It calls for the telecom industry to embrace the prospects of AIGC services and face the unique challenges posed by incorporating generative model services into the AI-native 6G wireless network paradigm. We propose enabling AIGC inference services on mobile devices by optimizing MEC-device computing offloading, through which AIGC task latency is minimized by reinforcement learning based policy agent in a computing resource constrained and bandwidth limited wireless environment. Simulation results are presented to demonstrate the performance advantage.
Original language | English (US) |
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Journal | IEEE Networking Letters |
DOIs | |
State | Accepted/In press - 2024 |
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Information Systems
- Communication
- Hardware and Architecture
Keywords
- 6G
- AIGC
- ChatGPT
- Constrained Reinforcement Learning
- LLM
- MEC
- On-device Computing