ABSTRACT
Multi-user MIMO (MU-MIMO) is a widely-known, fundamental technique to significantly improve the spectrum efficiency. While there is a great demand for spectrum efficiency and massive scalability under explosively increasing IoT, hardware limitations make it particularly challenging for the mechanism to be transferred to the IoT (e.g., ZigBee) domain. This paper presents X-MIMO, a zero-cost, software-only cross-technology MU-MIMO for commodity ZigBee. As the first work to shed the light on the feasibility of MU-MIMO on commodity IoT, X-MIMO leverages on cross-technology communication (CTC) to turn the pervasively-deployed WiFi AP into MU-MIMO transmitter, delivering different packets to multiple ZigBees in parallel. X-MIMO uniquely exploits WiFi CSI to extract the accurate physical layer signal of the ZigBee packet and the WiFi-ZigBee channel coefficient. Rigorous derivation shows that X-MIMO's precoding is inherently immune to the uncertainties of the commodity devices, making X-MIMO highly reliable in practice. Lastly, spectrum-efficient emulation is proposed to maximize the spectrum reuse. We implement and comprehensively evaluate the performance of X-MIMO on commodity devices (Atheros AR9334 WiFi NIC and TelosB CC2420) as well as on USRP B210 for in-depth analysis. Results reveal that X-MIMO achieves 495 Kbps with <1% symbol error rate (SER) and 704.24 Kbps with 6.1% SER for two and three streams, respectively. Near-linear increase of the throughput effectively demonstrates the feasibility of X-MIMO.
- CC2530 Datasheet. https://www.ti.com/product/CC2530.Google Scholar
- IEEE 802.11 Protocol. http://standards.ieee.org/getieee802/download/802.11-2012.pdf.Google Scholar
- IEEE 802.15.4 Protocol. http://standards.ieee.org/getieee802/download/802.15.4-2015.pdf.Google Scholar
- Implementation of IEEE 802.15.4 Protocol on USRP. https://github.com/bastibl/gr-ieee802-15-4.Google Scholar
- WirelessHART, an Industrial Wireless Technology. https://www.emerson.com/en-us/expertise/automation/industrial-internet-things/pervasive-sensing-solutions/wireless-technology.Google Scholar
- CC2420 Data Sheet. http://www.ti.com/lit/ds/symlink/cc2420.pdf, 2003.Google Scholar
- Isa standard, wireless systems for industrial automation: Process control and related applications. ISA-100.11 a-2009, 2009.Google Scholar
- Ieee standard for local and metropolitan area networks - part 15.4: Low-rate wireless personal area networks (lr-wpans) amendment 4: Alternative physical layer extension to support medical body area network (mban) services operating in the 2360 mhz - 2400 mhz band. IEEE Std 802.15.4j-2013 (Amendment to IEEE Std 802.15.4-2011 as amended by IEEE Std 802.15.4e-2012, IEEE Std 802.15.4f-2012, and IEEE Std 802.15.4g-2012), pages 1--24, 2013.Google Scholar
- B. Al Nahas, S. Duquennoy, and O. Landsiedel. Concurrent transmissions for multi-hop bluetooth 5. In EWSN, pages 130--141, 2019.Google Scholar
- J. Beysens, A. Galisteo, Q. Wang, D. Juara, D. Giustiniano, and S. Pollin. Densevlc: A cell-free massive mimo system with distributed leds. In Proceedings of the 14th International Conference on emerging Networking EXperiments and Technologies, pages 320--332, 2018.Google Scholar
Digital Library
- A. Bhartia, Y.-C. Chen, L. Qiu, and G. P. Nychis. Embracing distributed mimo in wireless meshnetworks. In 2015 IEEE 23rd International Conference on Network Protocols (ICNP), pages 66--77. IEEE, 2015.Google Scholar
Cross Ref
- M. Brachmann, O. Landsiedel, and S. Santini. Concurrent transmissions for communication protocols in the internet of things. In 2016 IEEE 41st Conference on Local Computer Networks (LCN), pages 406--414. IEEE, 2016.Google Scholar
Cross Ref
- J. Chan, A. Wang, V. Iyer, and S. Gollakota. Surface mimo: Using conductive surfaces for mimo between small devices. In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, pages 3--18, 2018.Google Scholar
Digital Library
- J. Chauhan, Y. Hu, S. Seneviratne, A. Misra, A. Seneviratne, and Y. Lee. Breathprint: Breathing acoustics-based user authentication. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, pages 278--291, 2017.Google Scholar
Digital Library
- B. Chen, V. Yenamandra, and K. Srinivasan. Tracking keystrokes using wireless signals. In Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services, pages 31--44, 2015.Google Scholar
Digital Library
- Z. Chen, G. Zhu, S. Wang, Y. Xu, J. Xiong, J. Zhao, J. Luo, and X. Wang. m3: Multipath assisted wi-fi localization with a single access point. IEEE Transactions on Mobile Computing, 2019.Google Scholar
Digital Library
- J. Ding and R. Chandra. Towards low cost soil sensing using wi-fi. In The 25th Annual International Conference on Mobile Computing and Networking, MobiCom '19, New York, NY, USA, 2019. Association for Computing Machinery.Google Scholar
- Y. Du, E. Aryafar, P. Cui, J. Camp, and M. Chiang. Samu: Design and implementation of selectivity-aware mu-mimo for wideband wifi. In 2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pages 229--237. IEEE, 2015.Google Scholar
Digital Library
- C. Gao, M. Hessar, K. Chintalapudi, and B. Priyantha. Blind distributed mu-mimo for iot networking over vhf narrowband spectrum. In The 25th Annual International Conference on Mobile Computing and Networking, pages 1--17, 2019.Google Scholar
Digital Library
- K. Geissdoerfer, R. Jurdak, B. Kusy, and M. Zimmerling. Getting more out of energy-harvesting systems: Energy management under time-varying utility with preact. In Proceedings of the 18th International Conference on Information Processing in Sensor Networks, pages 109--120, 2019.Google Scholar
Digital Library
- X. Guo, Y. He, J. Zhang, and H. Jiang. Wide: Physical-level ctc via digital emulation. In 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), pages 49--60. IEEE, 2019.Google Scholar
Digital Library
- X. Guo, Y. He, X. Zheng, L. Yu, and O. Gnawali. Zigfi: Harnessing channel state information for cross-technology communication. IEEE/ACM Transactions on Networking, 28(1):301--311, 2020.Google Scholar
Digital Library
- X. Guo, Y. He, X. Zheng, Z. Yu, and Y. Liu. Lego-fi: Transmitter-transparent ctc with cross-demapping. In IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pages 2125--2133. IEEE, 2019.Google Scholar
Digital Library
- E. Hamed, H. Rahul, and B. Partov. Chorus: truly distributed distributed-mimo. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, pages 461--475, 2018.Google Scholar
Digital Library
- M. Hammouda, R. Zheng, and T. N. Davidson. Full-duplex spectrum sensing and access in cognitive radio networks with unknown primary user activities. In 2016 IEEE International Conference on Communications (ICC), pages 1--6. IEEE, 2016.Google Scholar
Cross Ref
- P. Hillyard, A. Luong, A. S. Abrar, N. Patwari, K. Sundar, R. Farney, J. Burch, C. Porucznik, and S. H. Pollard. Experience: Cross-technology radio respiratory monitoring performance study. In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, pages 487--496, 2018.Google Scholar
Digital Library
- C. Hua, H. Yu, R. Zheng, J. Li, and R. Ni. Online packet dispatching for delay optimal concurrent transmissions in heterogeneous multi-rat networks. IEEE Transactions on Wireless Communications, 15(7):5076--5086, 2016.Google Scholar
Digital Library
- C. Husmann, G. Georgis, K. Nikitopoulos, and K. Jamieson. Flexcore: massively parallel and flexible processing for large mimo access points. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI), pages 197--211, 2017.Google Scholar
- V. Iyer, V. Talla, B. Kellogg, S. Gollakota, and J. Smith. Inter-technology backscatter: Towards internet connectivity for implanted devices. In Proceedings of the 2016 ACM SIGCOMM Conference, pages 356--369, 2016.Google Scholar
Digital Library
- W. Jiang, S. M. Kim, Z. Li, and T. He. Achieving receiver-side cross-technology communication with cross-decoding. In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, pages 639--652, 2018.Google Scholar
Digital Library
- W. Jiang, Z. Yin, R. Liu, Z. Li, S. M. Kim, and T. He. Bluebee: a 10,000 x faster cross-technology communication via phy emulation. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems, pages 1--13, 2017.Google Scholar
Digital Library
- K. Jin, S. Fang, C. Peng, Z. Teng, X. Mao, L. Zhang, and X. Li. Vivisnoop: Someone is snooping your typing without seeing it! In 2017 IEEE Conference on Communications and Network Security (CNS), pages 1--9. IEEE, 2017.Google Scholar
- V. Jungnickel, K. Manolakis, W. Zirwas, B. Panzner, V. Braun, M. Lossow, M. Sternad, R. Apelfröjd, and T. Svensson. The role of small cells, coordinated multipoint, and massive mimo in 5g. IEEE communications magazine, 52(5):44--51, 2014.Google Scholar
Cross Ref
- S. M. Kim and T. He. Freebee: Cross-technology communication via free side-channel. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, pages 317--330. ACM, 2015.Google Scholar
Digital Library
- H. Kong, L. Lu, J. Yu, Y. Chen, L. Kong, and M. Li. Fingerpass: Finger gesture-based continuous user authentication for smart homes using commodity wifi. In Proceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 201--210, 2019.Google Scholar
Digital Library
- Z. Li and T. He. Webee: Physical-layer cross-technology communication via emulation. In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking, pages 2--14, 2017.Google Scholar
Digital Library
- K. C.-J. Lin, S. Gollakota, and D. Katabi. Random access heterogeneous mimo networks. ACM SIGCOMM Computer Communication Review, 41(4):146--157, 2011.Google Scholar
Digital Library
- R. Liu, Z. Yin, W. Jiang, and T. He. Lte2b: time-domain cross-technology emulation under lte constraints. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems, pages 179--191, 2019.Google Scholar
Digital Library
- H. Lou, M. Ghosh, P. Xia, and R. Olesen. A comparison of implicit and explicit channel feedback methods for mu-mimo wlan systems. In 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pages 419--424. IEEE, 2013.Google Scholar
- A. R. Moghimi, H.-M. Tsai, C. U. Saraydar, and O. K. Tonguz. Characterizing intra-car wireless channels. IEEE Transactions on Vehicular Technology, 58(9):5299--5305, 2009.Google Scholar
Cross Ref
- H. S. Rahul, S. Kumar, and D. Katabi. Jmb: scaling wireless capacity with user demands. ACM SIGCOMM Computer Communication Review, 42(4):235--246, 2012.Google Scholar
Digital Library
- M. Sha, G. Xing, G. Zhou, S. Liu, and X. Wang. C-mac: Model-driven concurrent medium access control for wireless sensor networks. In IEEE INFOCOM 2009, pages 1845--1853. IEEE, 2009.Google Scholar
Cross Ref
- L. Shangguan, Z. Zhou, and K. Jamieson. Enabling gesture-based interactions with objects. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, pages 239--251, 2017.Google Scholar
Digital Library
- C. Shepard, H. Yu, N. Anand, E. Li, T. Marzetta, R. Yang, and L. Zhong. Argos: Practical many-antenna base stations. In Proceedings of the 18th annual international conference on Mobile computing and networking, pages 53--64, 2012.Google Scholar
Digital Library
- J. Song, S. Han, A. Mok, D. Chen, M. Lucas, M. Nixon, and W. Pratt. Wirelesshart: Applying wireless technology in real-time industrial process control. In 2008 IEEE Real-Time and Embedded Technology and Applications Symposium, pages 377--386. IEEE, 2008.Google Scholar
Digital Library
- P. Sparks. The route to a trillion devices. 2017.Google Scholar
- Q. H. Spencer, C. B. Peel, A. L. Swindlehurst, and M. Haardt. An introduction to the multi-user mimo downlink. IEEE communications Magazine, 42(10):60--67, 2004.Google Scholar
Digital Library
- S. Sur, I. Pefkianakis, X. Zhang, and K.-H. Kim. Practical mu-mimo user selection on 802.11 ac commodity networks. In Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, pages 122--134, 2016.Google Scholar
Digital Library
- H.-M. Tsai, O. K. Tonguz, C. Saraydar, T. Talty, M. Ames, and A. Macdonald. Zigbee-based intra-car wireless sensor networks: a case study. IEEE Wireless Communications, 14(6):67--77, 2007.Google Scholar
Digital Library
- G. Wang, C. Qian, K. Cui, H. Ding, H. Cai, W. Xi, J. Han, and J. Zhao. A (near) zero-cost and universal method to combat multipaths for rfid sensing. In 2019 IEEE 27th International Conference on Network Protocols (ICNP), pages 1--4. IEEE, 2019.Google Scholar
Cross Ref
- J. Wang, L. Chang, O. Abari, and S. Keshav. Are rfid sensing systems ready for the real world? In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys '19, pages 366--377, New York, NY, USA, 2019. Association for Computing Machinery.Google Scholar
Digital Library
- S. Wang, S. M. Kim, and T. He. Symbol-level cross-technology communication via payload encoding. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), pages 500--510. IEEE, 2018.Google Scholar
Cross Ref
- W. Wang, X. Zheng, Y. He, and X. Guo. Adacomm: Tracing channel dynamics for reliable cross-technology communication. In 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pages 1--9. IEEE, 2019.Google Scholar
Digital Library
- X. Xie, E. Chai, X. Zhang, K. Sundaresan, A. Khojastepour, and S. Rangarajan. Hekaton: Efficient and practical large-scale mimo. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, pages 304--316, 2015.Google Scholar
Digital Library
- X. Xie, X. Zhang, and K. Sundaresan. Adaptive feedback compression for mimo networks. In Proceedings of the 19th annual international conference on Mobile computing & networking, pages 477--488, 2013.Google Scholar
Digital Library
- Y. Xie, Z. Li, and M. Li. Precise power delay profiling with commodity wi-fi. IEEE Transactions on Mobile Computing, 18(6):1342--1355, 2018.Google Scholar
Digital Library
- M. Yang, L.-X. Chuo, K. Suri, L. Liu, H. Zheng, and H.-S. Kim. ilps: Local positioning system with simultaneous localization and wireless communication. In IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pages 379--387. IEEE, 2019.Google Scholar
Digital Library
- Q. Yang, X. Li, H. Yao, J. Fang, K. Tan, W. Hu, J. Zhang, and Y. Zhang. Bigstation: enabling scalable real-time signal processing in large mu-mimo systems. ACM SIGCOMM Computer Communication Review, 43(4):399--410, 2013.Google Scholar
Digital Library
- S. Yao, Y. Zhao, H. Shao, S. Liu, D. Liu, L. Su, and T. Abdelzaher. Fastdeepiot: Towards understanding and optimizing neural network execution time on mobile and embedded devices. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems, pages 278--291, 2018.Google Scholar
Digital Library
- S. Yao, Y. Zhao, A. Zhang, L. Su, and T. Abdelzaher. Deepiot: Compressing deep neural network structures for sensing systems with a compressor-critic framework. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems, pages 1--14, 2017.Google Scholar
Digital Library
- D. Zhang, J. Wang, J. Jang, J. Zhang, and S. Kumar. On the feasibility of wi-fi based material sensing. In The 25th Annual International Conference on Mobile Computing and Networking, pages 1--16, 2019.Google Scholar
Digital Library
- J. Zhang, X. Guo, H. Jiang, X. Zheng, and Y. He. Link quality estimation of cross-technology communication.Google Scholar
- X. Zhang, D. Yang, L. Shen, X. Chang, J. Huang, and G. Xing. Real-time power profiling of narrowband internet of things networks. In Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos, pages 90--92, 2019.Google Scholar
Digital Library
- M. Zhao, F. Adib, and D. Katabi. Emotion recognition using wireless signals. In Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, pages 95--108, 2016.Google Scholar
Digital Library
- X. Zheng, Y. He, and X. Guo. Stripcomm: Interference-resilient cross-technology communication in coexisting environments. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications, pages 171--179. IEEE, 2018.Google Scholar
Digital Library
- R. Zhou, Y. Xiong, G. Xing, L. Sun, and J. Ma. Zifi: wireless lan discovery via zigbee interference signatures. In Proceedings of the sixteenth annual international conference on Mobile computing and networking, pages 49--60, 2010.Google Scholar
Digital Library
- M. Zimmerling, W. Dargie, and J. M. Reason. Energy-efficient routing in linear wireless sensor networks. In 2007 IEEE International Conference on Mobile Adhoc and Sensor Systems, pages 1--3. IEEE, 2007.Google Scholar
Cross Ref
Index Terms
X-MIMO: cross-technology multi-user MIMO
Recommendations
A Novel CSI Feedback Method for Dynamic SU/MU MIMO Adaptation
Channel state information (CSI) reporting at one mobile station (MS) often targets maximizing the throughput of one single link, hence is optimized for single-user multi-input multi-output (SU-MIMO) transmission at base station (BS). However, the system ...
Cellular Downlink Performance with Covariance-CSIT-Based MIMO Precoding
The nature of the trade-off between reduced overhead of channel state information (CSI) and resultant performance losses influences the design of frequency-division duplexed practical cellular systems. One candidate for CSI feedback reduction is the use ...
Zero-forcing DPC beamforming design for multiuser MIMO broadcast channels
The sum rate maximization in multiuser MIMO broadcast channels is investigated in this paper. We first propose an approach under a total power constraint. Compared with the most related methods in the literature, the proposed method can be easily ...





Comments