.png){kind=icon}
返回
Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization
.png){kind=icon}
OA
AI
DOI：10.1109/TWC.2023.3285869.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Sensors
Task analysis
Resource management
Hardware
Delays
Servers
Wireless sensor networks
Integrated sensing and communication
mobile edge computing
resource allocation
action recognition
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
机构
引用论文
.png){kind=icon}
分享收藏
分享收藏
查看更多内容