Problem
Research questions and friction points this paper is trying to address.
Communication-driven multi-view sensing
Limited communication resources
Sensing acquisition and edge inference coupling
Source entropy
Source Entropy-Guided Adaptive Transmission for Communication-Driven Multi-View Sensing
🤖 AI Summary
为解决多视角感知中通信资源受限问题，提出了一种基于源熵指导的自适应传输框架，通过分析信道状态信息并选择合适的数据传输方式来优化边缘推理性能。
📝 Abstract
Communication-driven multi-view sensing relies on routine communication transmissions for sensing acquisition, while the resulting sensing data at distributed devices must be uploaded to an edge server under limited communication resources. This creates a unique coupling between sensing acquisition and edge inference: the communication interval determines the source information, whereas the uplink condition determines how much information can be delivered to the server for sensing inference. To account for this coupling, we propose a source entropy-guided adaptive transmission framework. Specifically, we characterize the entropy of packet-triggered channel state information (CSI) as a function of the communication interval using a multi-output Gaussian process. The resulting analytical bound is compared with the available bit budget, determined by the transmission rate and latency requirement, to select between original-data and task-oriented transmission. For task-oriented transmission, we formulate the communication-constrained inference problem based on the information bottleneck and decompose it into adaptive distributed encoding and multi-view inference (ADE-MI), which avoids alternating optimization between the devices and the edge server. Experiments on the Widar3.0 multi-view CSI gesture recognition dataset show that the analytical bound closely follows the normalizing-flow numerical estimate, while ADE-MI outperforms task-oriented benchmarks under the same bit budget and the proposed framework further improves recognition accuracy under time-varying channels.
Innovation
Methods, ideas, or system contributions that make the work stand out.
source entropy-guided adaptive transmission
multi-output Gaussian process
communication-constrained inference
adaptive distributed encoding and multi-view inference (ADE-MI)
information bottleneck
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