TY - GEN
T1 - Blind Signal Detection for Asynchronous Multi-Tag Transmission in Ambient Backscatter Communications
AU - Liu, Yuan
AU - Ren, Pinyi
AU - Xu, Dongyang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Ambient backscatter communications, a promising technique to realize massive machine type communication (mMTC), has recently attracted great attentions, due to its spectrum-and-energy-efficient characteristics. In ambient backscatter communications, multiple tags will transmit signals asynchronously to the target reader, which however imposes huge challenges to the radio access and signal detection at the reader. To tackle these problems, we propose an independent component analysis (ICA) based blind signal separation, identification and detection scheme. Specifically, each of tag signals is randomly and independently encoded to reduce the collision of the tags. Then a novel ICA algorithm is applied at the reader to separate, identify and detect the signals. The results show that the proposed scheme, compared with existing schemes, provides higher detection accuracy with lower cost even under a large number of tags.
AB - Ambient backscatter communications, a promising technique to realize massive machine type communication (mMTC), has recently attracted great attentions, due to its spectrum-and-energy-efficient characteristics. In ambient backscatter communications, multiple tags will transmit signals asynchronously to the target reader, which however imposes huge challenges to the radio access and signal detection at the reader. To tackle these problems, we propose an independent component analysis (ICA) based blind signal separation, identification and detection scheme. Specifically, each of tag signals is randomly and independently encoded to reduce the collision of the tags. Then a novel ICA algorithm is applied at the reader to separate, identify and detect the signals. The results show that the proposed scheme, compared with existing schemes, provides higher detection accuracy with lower cost even under a large number of tags.
KW - Independent Component Analysis (ICA)
KW - ambient backscatter communications
KW - multi-tag
KW - signal separation and identification
UR - https://www.scopus.com/pages/publications/85137831195
U2 - 10.1109/VTC2022-Spring54318.2022.9860476
DO - 10.1109/VTC2022-Spring54318.2022.9860476
M3 - 会议稿件
AN - SCOPUS:85137831195
T3 - IEEE Vehicular Technology Conference
BT - 2022 IEEE 95th Vehicular Technology Conference - Spring, VTC 2022-Spring - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 95th IEEE Vehicular Technology Conference - Spring, VTC 2022-Spring
Y2 - 19 June 2022 through 22 June 2022
ER -