Xiuzhen Guo 郭秀珍
                   Postdoc Researcher [CV]

                   guoxiuzhen94@gmail.com
 

 

 

 

 

 

 

 

 

 

 

School of Software, Tsinghua University, Beijing, P.R. China.

 

 

 

News!
  • [2023.06] Our survey paper on mmWave-based human sensing was accepted by IEEE communication survey & tutorial !
  • [2023.03] Our paper “Leggiero” on analog WiFi backscatter communication was accepted by ACM MobiSys 2023 !
  • [2023.01] I was invited to serve on the TPC of IEEE SECON 2023!
  • [2022.08] Our paper “RF-Transformer” on unified backscatter communication was accepted by ACM MobiCom 2022 !
  • [2022.07] Our paper “MotorBeat” on acoustic sensing was accepted by ACM UbiComp 2022 !
  • [2022.05] I was Invited to publicity co-chair of IEEE ICPADS 2022 !
  • [2022.03] I was Invited to submission chair of IEEE SECON 2022 !
  • [2022.03] Our survey paper on Cross-Technology Communication was accepted by ACM Computing Surveys !
  • [2021.12] I was recognized as 2021 ACM China Doctoral Dissertation Award !
  • [2021.12] Our paper "CurvingLoRa" on LoRa parallel transmission was accepted by USENIX NSDI 2022!
  • [2021.10] Our paper "Aloba" on backscatter communication was accepted by IEEE/ACM ToN !
  • [2021.09] Our paper "Palantir" on LoRa backscatter sensing was accepted by ACM SenSys 2021 !
  • [2021.06] Our paper "Saiyan" on LoRa backscatter systems was accepted by USENIX NSDI 2022!

Biography

I received my B.S. degree from the College of Electric and Information Engineering, Southwest University in 2016, the Ph.D. degree from the Department of Software, Tsinghua University in 2021. I am currently a Postdoc researcher in the Systems and Ubiquitous Networking (SUN) group in Tsinghua University, advised by Dr. Yuan He. My research interests include wireless networking, Internet of Things, and ubiquitous computing.

Research Interests
  • Wireless networking: Cross-technology communication; Wireless coexistence; Heterogeneous networking; Backscatter communication
  • Ubiquitous computing: Mobile sensing

Projects

  • RF-Transformer: A Unified Backscatter Radio Hardware Abstraction

    • This paper presents RF-Transformer, a unified backscatter radio hardware abstraction that allows a low-power IoT device to directly communicate with heterogeneous wireless receivers at the minimum power consumption. Unlike existing backscatter systems that are tailored to a specific wireless communication protocol, RF-Transformer provides a programmable interface to the micro-controller, allowing IoT devices to synthesize different types of protocol-compliant backscatter signals sharing radically different PHY-layer designs. To show the efficacy of our design, we implement a PCB prototype of RF-Transformer on 2.4 GHz ISM band and showcase its capability on generating standard ZigBee, Bluetooth, LoRa, andWi-Fi 802.11b/g/n/ac packets. Our extensive field studies show that RF-Transformer achieves 23.8 Mbps, 247.1 Kbps, 986.5 Kbps, and 27.3 Kbps throughput when generating standard Wi-Fi, ZigBee, Bluetooth, and LoRa signals while consuming 23–177× less power than their active counterparts. Our ASIC simulation based on the 65-nm CMOS process shows that the power gain of RF-Transformer can further grow to 187–3165×. We further integrate RF-Transformer with pressure sensors and present a case study on detecting foot traffic density in hallways. Our 7-day case studies demonstrate RF-Transformer can reliably transmit sensor data to a commodity gateway by synthesizing LoRa packets on top of Wi-Fi signals. Code and hardware schematics can be found at: https://github.com/LeFsCC/RF-Transformer. This work appears in the proceedings of ACM MobiCom 2022.

  • Saiyan: Design and Implementation of a Low-power Demodulator for LoRa Backscatter Systems.

    • The radio range of backscatter systems continues growing as new wireless communication primitives are continuously invented. Nevertheless, both the bit error rate and the packet loss rate of backscatter signals increase rapidly with the radio range, thereby necessitating the cooperation between the access point and the backscatter tags through a feedback loop. Unfortunately, the low-power nature of backscatter tags limits their ability to demodulate feedback signals from a remote access point and scales down to such circumstances. This paper presents Saiyan, an ultra-low-power demodulator for long-range LoRa backscatter systems. With Saiyan, a backscatter tag can demodulate feedback signals from a remote access point with moderate power consumption and then perform an immediate packet re-transmission in the presence of packet loss. Moreover, Saiyan enables rate adaption and channel hopping – two PHY-layer operations that are important to channel efficiency yet unavailable on long-range backscatter systems.We prototype Saiyan on a two-layer PCB board and evaluate its performance in different environments. Results show that Saiyan achieves 3.5–5X gain on the demodulation range, compared with state-of-the-art systems. Our ASIC simulation shows that the power consumption of Saiyan is around 93.2 μW. Code and hardware schematics can be found at: https://github.com/ZangJac/Saiyan. This work appears in the proceedings of USENIX NSDI 2022.

  • Aloba: Rethinking ON-OFF Keying Modulation for Ambient LoRa Backscatter

    • Backscatter communication holds potential for ubiquitous and low-cost connectivity among low-power IoT devices. To avoid interference between the carrier signal and the backscatter signal, recent works propose frequency-shifting technique to separate these two signals in frequency. Such proposals, however, have to occupy the precious wireless spectrum that is already overcrowded, and increase the power, cost, and complexity of tag design. We revisit the classic ON-OFF Keying (OOK) modulation and propose Aloba, a backscatter system that takes the ambient LoRa transmissions as the excitation and piggybacks the in-band OOK modulated signals over the LoRa transmissions. Our design enables the backsactter signal to work in the same frequency band of the carrier signal, meanwhile achieving good tradeoff between transmission range and link throughput. The key contributions of Aloba are: i) the design of a low-power backscatter tag that can pick up the ambient LoRa signals from other signals; ii) a novel decoding algorithm to demodulate both the carrier signal and the backscatter signal from their superposition. The design of ALoba completely unleashes the backscatter tag's ability in OOK modulation and achieves flexible data rate at different transmission range. Aloba can achieve 39.5--199.4 Kbps data rate at various distances. This work appears in the proceedings of ACM SenSys 2020.

  • Palantir: Accurate Mobile Sensing over a LoRa Backscatter Channel.

    • Wireless sensing, which acquires the information of a target by collecting and analyzing wireless signals, is a key enabling technology for ubiquitous Internet of Things applications. In the past decade, we have witnessed a large body of studies on wireless sensing. The wireless technologies for sensing range from acoustic, RFID and WiFi to LoRa and mmWave, while the sensing capabilities extensively cover motion and activity sensing, mobility measurement, environmental sensing, and material sensing, etc. However, how to sense the condition of a mobile target in a long range is still a missing piece. In this work, we present Palantir, a first-of-its-kind long-range sensing system based on the LoRa backscatter, for cyclists in the public bicycle sharing systems. For this purpose, we design a complete signal processing flow to particularly deal with multiple challenging problems that are coupled with each other, such as amplitude instability, frequency offset, clock drift, spectrum leakage, and multiplicative noise. We evaluate the performance of Palantir by performing comprehensive benchmark experiments. We also build a prototype and conduct a case study of respiration monitoring in the real world. The results demonstrate that Palantir performs accurate sensing at the range of 100 m with a median deviation of motion period to as low as 0.2%, and works well for mobile targets. This work appears in the proceedings of ACM SenSys 2021.

  • ZigFi: Harnessing Channel State Information for Cross-Technology Communication.

    • Over the last decade,we have witnessed the explosive growth of wireless technologies in diversity (e.g., WiFi, ZigBee, and Bluetooth) as well as in density, to satisfy various communication and service requirements under different environments. Under the highly diversified and dense wireless habitat, the connectivity between specialized heterogeneous wireless technologies offers a great opportunity for advanced services. To this end, researchers recently propose cross-technology communication (CTC) technique which enables direct connection between heterogeneities only using commodity devices. In this paper, we propose ZigFi, a novel CTC from ZigBee to WiFi. ZigFi deliberately overlaps ZigBee packets with WiFi packets and Channel State Information (CSI) is used to convey data. Evaluation results demonstrate that ZigFi achieves a throughput of 215.9bps, which is 18x faster than the state-of-the-art approach. This work appears in the proceedings of IEEE/ACM ToN 2020 and INFOCOM 2018.

  • WIDE: Physical-level CTC via Digital Emulation.

    • Recent works achieve physical-level CTC by emulating the standard time-domain waveform of the receiver. This method faces the challenges of inherent unreliability due to the imperfect emulation. Different from analog emulation, we propose a novel concept named digital emulation, which stems from the following insight: The receiver relies on the phase shift to decode symbols rather than the shape of analog time-domain waveform. There are lots of phase sequences which satisfy the requirement of phase shift. The distortions of these phase sequences after WiFi emulation are different. We have the opportunity to select an appropriate phase sequence with the relatively small emulation errors to achieve a reliable CTC. We implement our proposal as WIDE, a physical-level CTC via digital emulation from WiFi to ZigBee. Evaluation results show that WIDE significantly improves the Packet Reception Ratio (PRR) from 41.7% to 86.2%, which is 2× of WEBee’s, an existing representative physical-level CTC. This work appears in the proceedings of IEEE/ACM IPSN 2019.

  • LEGO-Fi: Harnessing Channel State Information for Cross-Technology Communication.

    • Existing physical-level CTC means considerable processing complexity at the transmitter, which doesn't apply to the communication from a low-end transmitter to a high-end receiver, e.g. from ZigBee to WiFi. This paper presents transmitter-transparent cross-technology communication, which leaves the processing complexity solely at the receiver side and therefore makes a critical advance toward bidirectional high-throughput CTC. We implement our proposal as LEGO-Fi, the communication from ZigBee to WiFi. The key technique inside is cross-demapping, which stems from two key technical insights: (1) A ZigBee packet leaves distinguishable features when passing the WiFi modules. (2) Compared to ZigBee’s simple encoding and modulation schemes, the rich processing capacity of WiFi offers extra flexibility to process a ZigBee packet. The evaluation results show that LEGO-Fi achieves a throughput of 213.6Kbps, which is respectively 13000× and 1200× faster than FreeBee and ZigFi, the two existing ZigBee-to-WiFi CTC approaches. This work appears in the proceedings of IEEE INFOCOM 2019.

  • WiZig: Harnessing Channel State Information for Cross-Technology Communication.

    • In order to achieve CTC, existing packet-level proposals try to exploit free side-channels as information carriers. Regarding the wireless medium, a side channel typically exists in the following three dimensions: frequency, amplitude, and time. By exploiting a side-channel like frequency, amplitude or time, the existing works enable CTC but have limited performance under channel noise. In this paper, we propose WiZig, a novel CTC technique that employs modulation techniques in both the amplitude and temporal dimensions to optimize the throughput over a noisy channel. We establish a theoretical model of the energy communication channel to clearly understand the channel capacity. We then devise an online rate adaptation algorithm to adjust the modulation strategy according to the channel condition. The evaluation results show that WiZig achieves a throughput of 153.85bps with less than 1% symbol error rate in a real noisy environment. This work appears in the proceedings of IEEE INFOCOM 2017.

  • Stripcomm: Harnessing Channel State Information for Cross-Technology Communication.

    • Existing packet-level CTCs based on amplitude modulation are not reliable in the coexisting environments. Although CTC can be free from the interference in the senders communication range by using RTS/CTS to reserve the channel, it is still easy for other ambient devices to introduce serious performance degradation of CTC. Considering the practice of IoT applications, how to make CTC resilient to interference is still an open problem. We propose StripComm, a novel CTC technique interconnecting WiFi and ZigBee devices in coexisting environments. We design a new interference-resilient modulation mechanism that encodes symbols by the changes of packet presence and absence to avoid the fallibility of the single state. We devise an interference-aware decoding mechanism that strips out the interference based on the distinguishable RSS patterns caused by the self-similarity of StripComm signals. The throughput of StripComm is 1.1Kbps with SER lower than 0.01 in a real office environment, and still 0.89Kbps even under strong interference.This work appears in the proceedings of IEEE INFOCOM 2018.

Publications
  • [MobiSys 2023] Xin Na, Xiuzhen Guo, Zihao Yu, Jia Zhang, Yuan He, Yunhao Liu, “Leggiero: Analog WiFi Backscatter with Payload Transparency”, MobiSys. [PDF]
  • [ACM CSUR] Yuan He, Xiuzhen Guo*, Xiaolong Zheng, Zihao Yu, Jia Zhang, Haotian Jiang, Xin Na, Jiacheng Zhang, “Cross-Technology Communication for the Internet of Things: A Survey”, ACM Comput. Surv. [PDF]
  • [MobiCom 2022] Xiuzhen Guo, Yuan He, Zihao Yu, Jiacheng Zhang, Yunhao Liu, Longfei Shangguan, "RF-Transformer: A Unified Backscatter Radio Hardware Abstraction", MobiCom. [PDF]
  • [NSDI 2022] Xiuzhen Guo, Longfei Shangguan, Yuan He, Nan Jing, Jiacheng Zhang, Haotian Jiang, Yunhao Liu, "Saiyan: Design and Implementation of a Low-power Demodulator for LoRa Backscatter Systems", NSDI. [PDF]
  • [NSDI 2022] Chenning Li, Xiuzhen Guo, Longfei Shangguan, Zhichao Cao, kyle Jamieson, "CurvingLoRa to Boost LoRa Network Throughput via Concurrent Transmission", NSDI.
  • [SenSys 2021] Haotian Jiang, Jiacheng Zhang, Xiuzhen Guo, Yuan He, "Sense Me on the Ride: Accurate Mobile Sensing over a LoRa Backscatter Channel", SenSys. [PDF]
  • [ToN 2021] Xiuzhen Guo, Longfei Shangguan, Yuan He, Jia Zhang, Haotian Jiang, Awais Ahmad Siddiqi, Yunhao Liu, "Efficient Ambient LoRa Backscatter with On-Off Keying Modulation", ToN. [PDF]
  • [ToN 2021] Xiuzhen Guo, Yuan He, Jia Zhang, Haotian Zhang, "WIDE: Physical-level CTC via Digital Emulation", ToN. [PDF]
  • [SenSys 2020] Xiuzhen Guo, Longfei Shangguan, Yuan He, Jia Zhang, Haotian Jiang, Awais Ahmad Siddiqi, Yunhao Liu, "Aloba: Rethinking ON-OFF Keying Modulation for Ambient LoRa Backscatter", SenSys. [PDF]
  • [ToN 2020] Xiuzhen Guo, Xiaolong Zheng, Yuan He, "Cross-Technology Energy Communication over a Noisy Channel", ToN. [PDF]
  • [ToN 2020] Xiuzhen Guo, Yuan He, Xiaolong Zheng, Liangcheng Yu, Omprakash Gnawali, "Harnessing Channel State Information for Cross-Technology Communication", ToN. [PDF]
  • [ToSN 2021] Xiuzhen Guo, Yuan He, Jia Zhang, Haotian Jiang, Zihao Yu, Xin Na, "Taming the Errors in Cross-Technology Communication: A Probabilistic Approach", ToSN. [PDF]
  • [IPSN 2019] Xiuzhen Guo, Yuan He, Jia Zhang, Haotian Jiang, "WIDE: Physical-level CTC via Digital Emulation", IPSN. [PDF]
  • [INFOCOM 2019] Xiuzhen Guo, Yuan He, Xiaolong Zheng, Zihao Yu, Yunhao Liu, "LEGO-Fi: Transmitter-Transparent CTC with Cross-Demapping", INFOCOM, Paris, France. [PDF]
  • [INFOCOM 2018] Xiuzhen Guo, Yuan He, Xiaolong Zheng, Liangcheng Yu, Omprakash Gnawali, "ZigFi: Harnessing Channel State Information for Cross-Technology Communication", INFOCOM, Honolulu, HI, USA. [PDF]
  • [INFOCOM 2017] Xiuzhen Guo, Xiaolong Zheng, Yuan He, "WiZig: Cross-Technology Energy Communication over a Noisy Channel", INFOCOM, Atlanta, GA, USA. [PDF]
  • [IoT Journal 2020] Xiuzhen Guo, Yuan He, Xiaolong Zheng, Zihao Yu, Yunhao Liu, "LEGOFi: Transmitter-Transparent CTC with Cross-Demapping", IEEE IoT Journal. [PDF]
  • [EWSN 2019] Xiuzhen Guo, "Cross Technology Communication in Heterogeneous Wireless Networks", EWSN PhD Forum, Beijing, China. [PDF]
  • [CWSN 2021] Jiacheng Zhang, Xiuzhen Guo, Yuan He, "Location Tracking over a LoRa Backscattering Channel", CWSN.
  • [SECON 2021] Xin Na, Xiuzhen Guo, Yuan He, "Wi-attack: Cross-technology Impersonation Attack against iBeacon Services", SECON.
  • [INFOCOM 2020] Jia Zhang, Xiuzhen Guo, Haotian Jiang, Xiaolong Zheng, Yuan He, "Link Quality Estimation of Cross Technology Communication", INFOCOM, Canada. [PDF]
  • [UbiComp 2022] Weiguo Wang, Jinming Li, Yuan He, Xiuzhen Guo, Yunhao Liu, "MotorBeat: Acoustic Communication for Home Appliances via Variable Pulse Width Modulation".
  • [MobiHoc 2020] Xiaolong Zheng, Dan Xia, Xiuzhen Guo, Liang Liu, Yuan He, Huadong Ma, "Link Quality Estimation of Cross Technology Communication", MobiHoc, Shanghai, China .
  • [SECON 2019] Weiguo Wang, Xiaolong Zheng, Yuan He, Xiuzhen Guo, "AdaComm: Tracing Channel Dynamics for Reliable Cross Technology Communication", SECON, Boston, MA, USA. [PDF]
  • [INFOCOM 2018] Xiaolong Zheng, Yuan He, Xiuzhen Guo, "Stripcomm: Interference-resilient crosstechnology communication in coexisting environments", INFOCOM, Honolulu, HI, USA. [PDF]
  • [ICDCS 2021] Zihao Yu, Pengyu Li, Carlo Alberto Boano, Yuan He, Meng Jin, Xiuzhen Guo, Xiaolong Zheng, "BiCord: Bidirectional Coordination among Coexisting Wireless Devices", ICDCS.
  • [EWSN 2018] Zihao Yu, Chengkun Jiang, Yuan He, Xiaolong Zheng, Xiuzhen Guo, "Crocs: Cross-Technology Clock Synchronization for WiFi and ZigBee", EWSN, Madrid, Spain. [PDF]
  • [MSN 2016] Shuo Lian, Xiuzhen Guo, Yuan He, Xu Zhao, "Error Scene Restoration with Runtime Logs of Wireless Sensor Networks", MSN, Hefei, China. [PDF]
  • [Sensors] Xiuzhen Guo, Chao Peng, Songlin Zhang, et al. A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance[J]. Sensors, 2015, 15(7):15198-15217.[PDF]
  • [Sensors] Yan Jia, Xiuzhen Guo, Shukai Duan, et al. Electronic Nose Feature Extraction Methods: A Review[J]. Sensors, 2015, 15(11):27804-27831.[PDF]

Contact
guoxz@mail.tsinghua.edu.cn