Mean Field Game-based Waveform Precoding Design for Mobile Crowd Integrated Sensing, Communication, and Computation Systems
Dezhi Wang, Chongwen Huang, Jiguang He, Xiaoming Chen, Wei Wang,, Zhaoyang Zhang, Zhu Han, M\'erouane Debbah

TL;DR
This paper introduces a mean field game-based waveform precoding algorithm for large-scale mobile crowd ISCC systems, effectively managing interactions among numerous ISAC devices to enhance communication and reduce costs.
Contribution
It proposes a novel MFG-based waveform precoding method tailored for large-scale ISCC systems, transforming complex device interactions into a mean field framework.
Findings
Improves communication performance compared to baseline methods.
Reduces the cost function in waveform precoding.
Efficiently handles large-scale device interactions.
Abstract
Data collection and processing timely is crucial for mobile crowd integrated sensing, communication, and computation~(ISCC) systems with various applications such as smart home and connected cars, which requires numerous integrated sensing and communication~(ISAC) devices to sense the targets and offload the data to the base station~(BS) for further processing. However, as the number of ISAC devices growing, there exists intensive interactions among ISAC devices in the processes of data collection and processing since they share the common network resources. In this paper, we consider the environment sensing problem in the large-scale mobile crowd ISCC systems and propose an efficient waveform precoding design algorithm based on the mean field game~(MFG). Specifically, to handle the complex interactions among large-scale ISAC devices, we first utilize the MFG method to transform the…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Radio Wave Propagation Studies
MethodsBalanced Selection
