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  2020, Vol. 1 Issue (2): 170-180    doi: 10.23919/ICN.2020.0013
    
Backscatter technologies and the future of Internet of Things: Challenges and opportunities
Chaochao Yao(),Yang Liu(),Xusheng Wei(),Gongpu Wang*(),Feifei Gao()
Beijing Key Lab of Transportation Data Analysis and Mining, School of Computer and Information Technology, Beiijing Jiaotong University, Beijing 100044, China
Beijing Institute of Aerospace Control Devices, Beijing 100854, China
VIVO Mobile Company, Beijing 100015, China
Department of Automation, Tsinghua University, Beijing 100084, China
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Abstract  

Energy source and circuit cost are two critical challenges for the future development of the Internet of Things (IoT). Backscatter communications offer a potential solution to conveniently obtain power and reduce cost for sensors in IoT, and researchers are paying close attention to the technology. Backscatter technology originated from the Second World War and has been widely applied in the logistics domain. Recently, both the academic and industrial worlds are proposing a series of new types of backscatter technologies for communications and IoT. In this paper, we review the history of both IoT and backscatter, describe the new types of backscatter, demonstrate their applications, and discuss the open challenges.



Key wordsambient backscatter      backscatter communications      battery-less sensor      Internet of Things (IoT)      Large Intelligent Surface (LIS)      Unmanned Aerial Vehicle (UAV)     
Received: 13 May 2020      Online: 19 August 2021
Fund:  Fundamental Research Funds for the Central Universities(2020YJS044);National Natural Science Foundation of China(61871026)
Corresponding Authors: Gongpu Wang     E-mail: chaochaoyao@bjtu.edu.cn;11111011@bjtu.edu.cn;xusheng.wei@vivo.com;gpwang@bjtu.edu.cn;feifeigao@ieee.org
About author: Chaochao Yao received the BS degree in computer science and technology from Anhui University, Hefei, China in 2019. He is currently a master student at the School of Computer and Information Technology, Beijing Jiaotong University. His research interests include signal processing, 5G communication technologies, and machine learning.|Yang Liu received the BS and PhD degrees from Beijing Jiaotong University, Beijing, China in 2012 and 2017, respectively. After graduation, he joined Beijing Institute of Aerospace Control Devices, Beijing, China. His current research interests are in the field of detection theory, spectrum sensing algorithm and performance analysis for cognitive radio networks, and ambient backscatter communication systems.|Xusheng Wei received the BS degree from Nanjing University, China in 1997, the MS degree from Tianjin University, China in 2000, and the PhD degree from the University of Edinburgh, UK in 2005. Since 2000, he has engaged in 2G/3G/4G/5G standardizations and various research/management positions at ZTE (Shanghai), HuaWei (Beijing), Philips Lab. UK, and Blackberry UK. Since 2014, he has worked as a principal consultant for Sharp Lab. UK and Fujitsu EU Lab. (UK). He joined VIVO in 2019 and engages in 5G standardization and 6G initiative. His research interests include wireless communication theory, signal processing, and Internet of Things.|Gongpu Wang received the BS degree in communication engineering from Anhui University, Hefei, China in 2001, the MS degree from Beijing University of Posts and Telecommunications (BUPT), Beijing, China in 2004, and the PhD degree from the University of Alberta, Edmonton, Canada in 2011. From 2004 to 2007, he was an assistant professor at the School of Network Education, BUPT. In 2011 he joined the School of Computer and Information Technology, Beijing Jiaotong University, China, where he is currently a full professor. His research interests include Internet of Things, wireless communication theory, and signal processing technologies.|Feifei Gao received the BE degree from Xi’an Jiaotong University, Xi’an, China in 2002, the MS degree from McMaster University, Hamilton, Canada in 2004, and the PhD degree from National University of Singapore, Singapore in 2007. He was a research fellow at the Institute for Infocomm Research (I2R), Agency for Science, Technology and Research, Singapore in 2008 and an assistant professor at the School of Engineering and Science, Jacobs University, Bremen, Germany from 2009 to 2010. In 2011, he joined the Department of Automation, Tsinghua University, Beijing, China, where he is currently an associate professor. His research areas include communication theory, signal processing for communications, array signal processing, and convex optimizations, with particular interests in MIMO techniques, multi-carrier communications, cooperative communication, and cognitive radio networks.|He has authored/coauthored more than 120 refereed IEEE journal papers and more than 120 IEEE conference proceeding papers. He has served as an editor of IEEE Transactions on Wireless Communications, IEEE Signal Processing Letters, IEEE Communications Letters, IEEE Wireless Communications Letters, International Journal on Antennas and Propagations, and China Communications. He has also served as the symposium co-chair for 2018 IEEE Vehicular Technology Conference Spring (VTC), 2015 IEEE Conference on Communications (ICC), 2014 IEEE Global Communications Conference (GLOBECOM), 2014 IEEE Vehicular Technology Conference Fall (VTC), as well as technical committee members for many other IEEE conferences. He was elected to the IEEE Fellows Class of 2020.
Cite this article:

Chaochao Yao,Yang Liu,Xusheng Wei,Gongpu Wang,Feifei Gao. Backscatter technologies and the future of Internet of Things: Challenges and opportunities. , 2020, 1: 170-180.

URL:

http://icn.tsinghuajournals.com/10.23919/ICN.2020.0013     OR     http://icn.tsinghuajournals.com/Y2020/V1/I2/170

Fig. 1 Milestone events of the IoT development.
Fig. 2 Number of academic papers on backscatter and ambient backscatter.
Fig. 3 Typical models for backscatter communication systems (BD means backscatter device).
Fig. 4 System structure for a reader and a digital/analog tag.
Fig. 5 Smart home architecture.
Fig. 6 Typical models for UAV-aided backscatter systems.
Fig. 7 Multiple access algorithms.
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