Integrated Sensing-Communication-Computation for Edge Artificial Intelligence

• URL: http://arxiv.org/abs/2306.01162v2
• Date: Thu, 18 Apr 2024 10:04:16 GMT
• Title: Integrated Sensing-Communication-Computation for Edge Artificial Intelligence
• Authors: Dingzhu Wen, Xiaoyang Li, Yong Zhou, Yuanming Shi, Sheng Wu, Chunxiao Jiang,
• Abstract summary: Integrated sensing-communication-computation (I SCC) is of paramount significance for improving resource utilization. This article presents various kinds of I SCC schemes for federated edge learning tasks and edge AI inference tasks in both application and physical layers.
• Score: 41.611639821262415
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Edge artificial intelligence (AI) has been a promising solution towards 6G to empower a series of advanced techniques such as digital twins, holographic projection, semantic communications, and auto-driving, for achieving intelligence of everything. The performance of edge AI tasks, including edge learning and edge AI inference, depends on the quality of three highly coupled processes, i.e., sensing for data acquisition, computation for information extraction, and communication for information transmission. However, these three modules need to compete for network resources for enhancing their own quality-of-services. To this end, integrated sensing-communication-computation (ISCC) is of paramount significance for improving resource utilization as well as achieving the customized goals of edge AI tasks. By investigating the interplay among the three modules, this article presents various kinds of ISCC schemes for federated edge learning tasks and edge AI inference tasks in both application and physical layers.

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