Collaborative Edge AI Inference over Cloud-RAN

doi:10.1109/TCOMM.2024.3388488

	Collaborative Edge AI Inference over Cloud-RAN
	Pengfei Zhang1 ; Dingzhu Wen1 ; Guangxu Zhu 2; Qimei Chen 3; Kaifeng Han 4; Yuanming Shi1
	2024
发表期刊	IEEE TRANSACTIONS ON COMMUNICATIONS (IF:7.2[JCR-2023],6.3[5-Year])
ISSN	1558-0857
EISSN	1558-0857
卷号	PP 期号:99 页码:1-1
发表状态	已发表
DOI	10.1109/TCOMM.2024.3388488
摘要	In this paper, a cloud radio access network (Cloud-RAN) based collaborative edge AI inference architecture is proposed. Specifically, geographically distributed devices capture real-time noise-corrupted sensory data samples and extract the noisy local feature vectors, which are then aggregated at each remote radio head (RRH) to suppress sensing noise. To realize efficient uplink feature aggregation, we allow each RRH receives local feature vectors from all devices over the same resource blocks simultaneously by leveraging an over-the-air computation (AirComp) technique. Thereafter, these aggregated feature vectors are quantized and transmitted to a central processor (CP) for further aggregation and downstream inference tasks. Our aim in this work is to maximize the inference accuracy via a surrogate accuracy metric called discriminant gain, which measures the discernibility of different classes in the feature space. The key challenges lie on simultaneously suppressing the coupled sensing noise, AirComp distortion caused by hostile wireless channels, and the quantization error resulting from the limited capacity of fronthaul links. To address these challenges, this work proposes a joint transmit precoding, receive beamforming, and quantization error control scheme to enhance the inference accuracy. Extensive numerical experiments demonstrate the effectiveness and superiority of our proposed optimization algorithm compared to various baselines. IEEE
关键词	Cloud radio access network edge AI edge inference over-the-air computation
URL	查看原文
收录类别	SCI ; EI
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20241715954218
EI主题词	Computer architecture
EI分类号	716.3 Radio Systems and Equipment
原始文献类型	Article in Press
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/364615
专题	信息科学与技术学院信息科学与技术学院_PI研究组_石远明组信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_文鼎柱组
通讯作者	Dingzhu Wen
作者单位	1.the School of Information Science and Technology, Network Intelligence Center, ShanghaiTech University, Shanghai, China 2.Shenzhen Research Institute of Big Data, Shenzhen, China 3.School of Electronic Information, Wuhan University, Wuhan, China 4.China Academy of Information and Communications Technology, Beijing, China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Pengfei Zhang,Dingzhu Wen,Guangxu Zhu,et al. Collaborative Edge AI Inference over Cloud-RAN[J]. IEEE TRANSACTIONS ON COMMUNICATIONS,2024,PP(99):1-1.
APA	Pengfei Zhang,Dingzhu Wen,Guangxu Zhu,Qimei Chen,Kaifeng Han,&Yuanming Shi.(2024).Collaborative Edge AI Inference over Cloud-RAN.IEEE TRANSACTIONS ON COMMUNICATIONS,PP(99),1-1.
MLA	Pengfei Zhang,et al."Collaborative Edge AI Inference over Cloud-RAN".IEEE TRANSACTIONS ON COMMUNICATIONS PP.99(2024):1-1.