WiZig: Cross-Technology Energy Communication Over a Noisy Channel

The proliferation of IoT applications brings the demand of ubiquitous connections among heterogeneous wireless devices. Cross-Technology Communication (CTC) is a significant technique to directly exchange data among heterogeneous devices that follow different standards. By exploiting a side-channel like frequency, amplitude, or temporal modulation, the existing works enable CTC but have limited performance under channel noise. In this article, we propose WiZig, a novel CTC technique from WiFi to ZigBee that employs modulations 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. Based on the theoretical model, WiZig controls the number of encoded energy amplitudes and the length of a receiving window, so as to optimize the CTC throughput. We implement a prototype of WiZig on a software radio platform and a commercial ZigBee device. The evaluation shows that WiZig achieves a throughput of 153.85bps with less than 1% symbol error rate in a real environment.

[1]  Tian He,et al.  FreeBee: Cross-technology Communication via Free Side-channel , 2015, MobiCom.

[2]  Kameswari Chebrolu,et al.  Esense: communication through energy sensing , 2009, MobiCom '09.

[3]  Nathalie Mitton,et al.  Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms , 2017, Trans. Emerg. Telecommun. Technol..

[4]  Eduard Alarcón,et al.  On signaling power: Communications over wireless energy , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[5]  Wei Dong,et al.  Accurate and Generic Sender Selection for Bulk Data Dissemination in Low-Power Wireless Networks , 2017, IEEE/ACM Transactions on Networking.

[6]  Yuan He,et al.  Link Quality Estimation of Cross-Technology Communication , 2020, IEEE INFOCOM 2020 - IEEE Conference on Computer Communications.

[7]  Kang G. Shin,et al.  Gap Sense: Lightweight coordination of heterogeneous wireless devices , 2013, 2013 Proceedings IEEE INFOCOM.

[8]  Carlo Alberto Boano,et al.  Demo: Cross-Technology Communication between BLE and Wi-Fi using Commodity Hardware , 2017, EWSN.

[9]  Yunhao Liu,et al.  Interference Resilient Duty Cycling for Sensor Networks Under Co-Existing Environments , 2017, IEEE Transactions on Communications.

[10]  Antonio Pescapè,et al.  A tool for the generation of realistic network workload for emerging networking scenarios , 2012, Comput. Networks.

[11]  Kang G. Shin,et al.  Adaptive Subcarrier Nulling: Enabling partial spectrum sharing in wireless LANs , 2011, 2011 19th IEEE International Conference on Network Protocols.

[12]  Andreas Terzis,et al.  Surviving wi-fi interference in low power ZigBee networks , 2010, SenSys '10.

[13]  D. Staelin Fast folding algorithm for detection of periodic pulse trains , 1969 .

[14]  Zhijun Li,et al.  BlueBee: a 10,000x Faster Cross-Technology Communication via PHY Emulation , 2017, SenSys.

[15]  Rong Zheng,et al.  WiCop: Engineering WiFi Temporal White-Spaces for Safe Operations of Wireless Personal Area Networks in Medical Applications , 2014 .

[16]  Yuan He,et al.  StripComm: Interference-Resilient Cross-Technology Communication in Coexisting Environments , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications.

[17]  Kang G. Shin,et al.  Enabling coexistence of heterogeneous wireless systems: case for ZigBee and WiFi , 2011, MobiHoc '11.

[18]  Alberto Cerpa,et al.  Thermovote: participatory sensing for efficient building HVAC conditioning , 2012, BuildSys@SenSys.

[19]  Rui Zhang,et al.  Wireless Information and Power Transfer: Architecture Design and Rate-Energy Tradeoff , 2012, IEEE Transactions on Communications.

[20]  Joshua R. Smith,et al.  Inter-Technology Backscatter: Towards Internet Connectivity for Implanted Devices , 2016, SIGCOMM.

[21]  Zhiwei Zhao,et al.  Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless Networks , 2020, IEEE/ACM Transactions on Networking.

[22]  Konstantin Mikhaylov,et al.  Extensible modular wireless sensor and actuator network and IoT platform with plug&play module connection , 2015, IPSN.

[23]  Liang Liu,et al.  Portal: transparent cross-technology opportunistic forwarding for low-power wireless networks , 2020, MobiHoc.

[24]  Sokol Kosta,et al.  Supporting interoperability of things in IoT systems , 2013, SenSys '13.

[25]  Yunhao Liu,et al.  ZiSense: towards interference resilient duty cycling in wireless sensor networks , 2014, SenSys.

[26]  Qun Li,et al.  HoWiES: A holistic approach to ZigBee assisted WiFi energy savings in mobile devices , 2013, 2013 Proceedings IEEE INFOCOM.

[27]  Yuan He,et al.  ZIGFI: Harnessing Channel State Information for Cross-Technology Communication , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications.

[28]  Prabal Dutta,et al.  The Internet of Things Has a Gateway Problem , 2015, HotMobile.

[29]  Wei Dong,et al.  Embracing Corruption Burstiness: Fast Error Recovery for ZigBee under Wi-Fi Interference , 2017, IEEE Transactions on Mobile Computing.

[30]  Justine Sherry,et al.  Silo: Predictable Message Latency in the Cloud , 2015, Comput. Commun. Rev..

[31]  Qiang Li,et al.  Interconnecting WiFi Devices with IEEE 802.15.4 Devices without Using a Gateway , 2015, 2015 International Conference on Distributed Computing in Sensor Systems.

[32]  Liang Liu,et al.  c-Chirp: Towards Symmetric Cross-technology Communication over Asymmetric Channels , 2020, 2020 17th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).