TY - GEN
T1 - A PCA Acceleration Algorithm For WiFi Sensing And Its Hardware Implementation
AU - Wang, He
AU - Wang, Qitong
AU - Huang, Leilei
AU - Shi, Chunqi
AU - Zhang, Runxi
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Currently, we are entering the wearable internet era. The use of WiFi signals to perceive human activities or changes in vital signs has gradually become a topic that people are enthusiastic about. Principal Component Analysis (PCA), as a universal data dimensionality reduction algorithm, has been widely applied in the field of WiFi sensing. It is utilized to expedite data processing time and enhance real-time detection capabilities. This paper proposes an acceleration algorithm for PCA in the field of WiFi sensing along with its corresponding hardware architecture. The experimental results indicate that the accuracy of this algorithm can reach 0.9965, and the processing time is approximately 10 ms. Based on the TSMC 22nm technology, the Design Complier (DC) results show that the data throughput of this hardware architecture can reach 24 Gbps@800M, with a gate count of 7571, and the power consumption is 1.6321mW.
AB - Currently, we are entering the wearable internet era. The use of WiFi signals to perceive human activities or changes in vital signs has gradually become a topic that people are enthusiastic about. Principal Component Analysis (PCA), as a universal data dimensionality reduction algorithm, has been widely applied in the field of WiFi sensing. It is utilized to expedite data processing time and enhance real-time detection capabilities. This paper proposes an acceleration algorithm for PCA in the field of WiFi sensing along with its corresponding hardware architecture. The experimental results indicate that the accuracy of this algorithm can reach 0.9965, and the processing time is approximately 10 ms. Based on the TSMC 22nm technology, the Design Complier (DC) results show that the data throughput of this hardware architecture can reach 24 Gbps@800M, with a gate count of 7571, and the power consumption is 1.6321mW.
KW - Acceleration algorithm
KW - Hardware architecture
KW - PCA
KW - WiFi sensing
UR - https://www.scopus.com/pages/publications/85198515608
U2 - 10.1109/ISCAS58744.2024.10557859
DO - 10.1109/ISCAS58744.2024.10557859
M3 - 会议稿件
AN - SCOPUS:85198515608
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - ISCAS 2024 - IEEE International Symposium on Circuits and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Symposium on Circuits and Systems, ISCAS 2024
Y2 - 19 May 2024 through 22 May 2024
ER -