research-article

X-MIMO: cross-technology multi-user MIMO

Authors:

Song Min KimAuthors Info & Claims

SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems

Pages 218 - 231

https://doi.org/10.1145/3384419.3430723

Published: 16 November 2020 Publication History

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.

References

[1]

CC2530 Datasheet. https://www.ti.com/product/CC2530.

[2]

IEEE 802.11 Protocol. http://standards.ieee.org/getieee802/download/802.11-2012.pdf.

[3]

IEEE 802.15.4 Protocol. http://standards.ieee.org/getieee802/download/802.15.4-2015.pdf.

[4]

Implementation of IEEE 802.15.4 Protocol on USRP. https://github.com/bastibl/gr-ieee802-15-4.

[5]

WirelessHART, an Industrial Wireless Technology. https://www.emerson.com/en-us/expertise/automation/industrial-internet-things/pervasive-sensing-solutions/wireless-technology.

[6]

CC2420 Data Sheet. http://www.ti.com/lit/ds/symlink/cc2420.pdf, 2003.

[7]

Isa standard, wireless systems for industrial automation: Process control and related applications. ISA-100.11 a-2009, 2009.

[8]

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.

[9]

B. Al Nahas, S. Duquennoy, and O. Landsiedel. Concurrent transmissions for multi-hop bluetooth 5. In EWSN, pages 130--141, 2019.

[10]

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.

Digital Library

[11]

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.

[12]

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.

[13]

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.

Digital Library

[14]

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.

Digital Library

[15]

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.

Digital Library

[16]

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.

Digital Library

[17]

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.

[18]

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.

Digital Library

[19]

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.

Digital Library

[20]

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.

Digital Library

[21]

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.

Digital Library

[22]

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.

Digital Library

[23]

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.

[24]

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.

Digital Library

[25]

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.

[26]

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.

Digital Library

[27]

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.

Digital Library

[28]

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.

[29]

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.

Digital Library

[30]

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.

Digital Library

[31]

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.

Digital Library

[32]

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.

[33]

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.

[34]

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.

Digital Library

[35]

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.

Digital Library

[36]

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.

Digital Library

[37]

K. C.-J. Lin, S. Gollakota, and D. Katabi. Random access heterogeneous mimo networks. ACM SIGCOMM Computer Communication Review, 41(4):146--157, 2011.

Digital Library

[38]

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.

Digital Library

[39]

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.

[40]

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.

[41]

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.

Digital Library

[42]

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.

[43]

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.

Digital Library

[44]

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.

Digital Library

[45]

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.

Digital Library

[46]

P. Sparks. The route to a trillion devices. 2017.

[47]

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.

Digital Library

[48]

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.

Digital Library

[49]

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.

Digital Library

[50]

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.

[51]

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.

Digital Library

[52]

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.

[53]

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.

[54]

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.

Digital Library

[55]

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.

Digital Library

[56]

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.

Digital Library

[57]

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.

Digital Library

[58]

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.

Digital Library

[59]

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.

Digital Library

[60]

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.

Digital Library

[61]

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.

Digital Library

[62]

J. Zhang, X. Guo, H. Jiang, X. Zheng, and Y. He. Link quality estimation of cross-technology communication.

[63]

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.

Digital Library

[64]

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.

Digital Library

[65]

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.

[66]

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.

Digital Library

[67]

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.

Cited By

Xia XHou NZheng YGu T(2023)PCube: Scaling LoRa Concurrent Transmissions with Reception DiversitiesACM Transactions on Sensor Networks10.1145/354557118:4(1-25)Online publication date: 7-Mar-2023
https://dl.acm.org/doi/10.1145/3545571
Wang WLiu XYao YChi ZRay SZhu TZhang Y(2023)Simultaneous Data Dissemination Among WiFi and ZigBee DevicesIEEE/ACM Transactions on Networking10.1109/TNET.2023.324307031:6(2545-2558)Online publication date: Dec-2023
https://doi.org/10.1109/TNET.2023.3243070
Alomari MMahmoud MRamli R(2022)A Systematic Review on the Energy Efficiency of Dynamic Clustering in a Heterogeneous Environment of Wireless Sensor Networks (WSNs)Electronics10.3390/electronics1118283711:18(2837)Online publication date: 8-Sep-2022
https://doi.org/10.3390/electronics11182837
Show More Cited By

Index Terms

X-MIMO: cross-technology multi-user MIMO
1. Networks
  1. Network types
    1. Wireless access networks
      1. Wireless local area networks

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

Information & Contributors

Information

Published In

cover image ACM Conferences

SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems

November 2020

852 pages

ISBN:9781450375900

DOI:10.1145/3384419

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 November 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Science Foundation

Conference

SenSys '20

Sponsor:

SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems

November 16 - 19, 2020

Virtual Event, Japan

Acceptance Rates

Overall Acceptance Rate 174 of 867 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
894
Total Downloads

Downloads (Last 12 months)79
Downloads (Last 6 weeks)10

Reflects downloads up to 07 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Xia XHou NZheng YGu T(2023)PCube: Scaling LoRa Concurrent Transmissions with Reception DiversitiesACM Transactions on Sensor Networks10.1145/354557118:4(1-25)Online publication date: 7-Mar-2023
https://dl.acm.org/doi/10.1145/3545571
Wang WLiu XYao YChi ZRay SZhu TZhang Y(2023)Simultaneous Data Dissemination Among WiFi and ZigBee DevicesIEEE/ACM Transactions on Networking10.1109/TNET.2023.324307031:6(2545-2558)Online publication date: Dec-2023
https://doi.org/10.1109/TNET.2023.3243070
Alomari MMahmoud MRamli R(2022)A Systematic Review on the Energy Efficiency of Dynamic Clustering in a Heterogeneous Environment of Wireless Sensor Networks (WSNs)Electronics10.3390/electronics1118283711:18(2837)Online publication date: 8-Sep-2022
https://doi.org/10.3390/electronics11182837
Feng CXia T(2022)High-Throughput Cross-Technology Communication via Chip-Level Side ChannelApplied Sciences10.3390/app1211561612:11(5616)Online publication date: 1-Jun-2022
https://doi.org/10.3390/app12115616
Chen RGao WBulusu NAryafar EBalasubramanian ASong J(2022)TransFiProceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services10.1145/3498361.3538946(357-370)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1145/3498361.3538946
Yan JCheng SLi ZLiu J(2022)PCTC: Parallel Cross Technology Communication in Heterogeneous wireless systems2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)10.1109/IPSN54338.2022.00013(67-78)Online publication date: May-2022
https://doi.org/10.1109/IPSN54338.2022.00013
Zhang ZChen WWang JWang SHe T(2022)CONST: Exploiting Spatial-Temporal Correlation for Multi-Gateway based Reliable LoRa Reception2022 IEEE 30th International Conference on Network Protocols (ICNP)10.1109/ICNP55882.2022.9940424(1-11)Online publication date: 30-Oct-2022
https://doi.org/10.1109/ICNP55882.2022.9940424
Wu HGao X(2021)Multimodal Data Based Regression to Monitor Air Pollutant Emission in FactoriesSustainability10.3390/su1305266313:5(2663)Online publication date: 2-Mar-2021
https://doi.org/10.3390/su13052663
Shi JMu DSha M(2021)Enabling Cross-technology Communication from LoRa to ZigBee via Payload Encoding in Sub-1 GHz BandsACM Transactions on Sensor Networks10.1145/347045218:1(1-26)Online publication date: 5-Oct-2021
https://dl.acm.org/doi/10.1145/3470452
Xia XHou NZheng YGu T(2021)PCubeProceedings of the 27th Annual International Conference on Mobile Computing and Networking10.1145/3447993.3483268(670-683)Online publication date: 25-Oct-2021
https://dl.acm.org/doi/10.1145/3447993.3483268

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents