Computer Science > Information Theory
[Submitted on 8 Nov 2022 (v1), last revised 6 Jun 2023 (this version, v3)]
Title:Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization
View PDFAbstract:Integrated sensing, computation, and communication (ISCC) has been recently considered as a promising technique for beyond 5G systems. In ISCC systems, the competition for communication and computation resources between sensing tasks for ambient intelligence and computation tasks from mobile devices becomes an increasingly challenging issue. To address it, we first propose an efficient sensing framework with a novel action detection module. In this module, a threshold is used for detecting whether the sensing target is static and thus the overhead can be reduced. Subsequently, we mathematically analyze the sensing performance of the proposed framework and theoretically prove its effectiveness with the help of the sampling theorem. Based on sensing performance models, we formulate a sensing performance maximization problem while guaranteeing the quality-of-service (QoS) requirements of tasks. To solve it, we propose an optimal resource allocation strategy, in which the minimum resource is allocated to computation tasks, and the rest is devoted to the sensing task. Besides, a threshold selection policy is derived and the results further demonstrate the necessity of the proposed sensing framework. Finally, a real-world test of action recognition tasks based on USRP B210 is conducted to verify the sensing performance analysis. Extensive experiments demonstrate the performance improvement of our proposal by comparing it with some benchmark schemes.
Submission history
From: Yinghui He [view email][v1] Tue, 8 Nov 2022 05:55:52 UTC (940 KB)
[v2] Wed, 9 Nov 2022 10:58:48 UTC (940 KB)
[v3] Tue, 6 Jun 2023 11:46:14 UTC (4,619 KB)
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