NnD: Shallow Neural Network Based Collision Decoding in IoT Communications

  • Zhe Wang
  • Linghe KongEmail author
  • Guihai Chen
  • Ming Ni
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11910)


Internet of Things (IoT) has been widely used in intelligent warehouse, environment monitoring and smart buildings. In these application scenarios, concurrent transmissions frequently occur in which multiple transmitters send packets to one receiver simultaneously, causing severe collisions and low throughput. The state-of-the-art methods are able to decompose collided packets from different transmitters. However, they rely heavily on random time offsets and has poor performance under inferior channel conditions. In this paper, we present a new physical layer mechanism Open image in new window (nnD) to resolve multi-packet collisions. We first collect collision-free symbols or history single packets as the training set. In order to improve the decoding accuracy, we model the mapping relationship between overlapped symbols and their symbol values by neural networks. Since overlapping combinations of symbols are limited which are decided by corresponding chips’ value, we can predict values of unknown symbols by classifying different kinds of overlapping combinations. By introducing neural networks, nnD can not only achieve a high decoding precision but also can dynamically choose neural network architecture to adapt to different collision scenarios. To evaluate the performance of nnD, extensive trace-driven simulations are conducted. The results demonstrate that nnD outperforms existing methods in terms of bit error rate and the number of concurrent transmissions.



This work was supported in part by the National Key R&D Program of China 2018YFB1004703, NSFC grant 61972253, 61672349, 61672353.


  1. 1.
    Alliance, Z.: Introduction to Zigbee (2018).
  2. 2.
    Gollakota, S., Katabi, D.: Zigzag decoding: combating hidden terminals in wireless networks. In: ACM SIGCOMM (2008)Google Scholar
  3. 3.
    Halperin, D., Hu, W., Sheth, A., Wetherall, D.: Predictable 802.11 packet delivery from wireless channel measurements. In: ACM SIGCOMM (2010)Google Scholar
  4. 4.
    Jabbar, S., Khan, M., Silva, B.N., Han, K.: A REST-based industrial web of things’ framework for smart warehousing. J. Supercomput. 74, 4419–4433 (2018)CrossRefGoogle Scholar
  5. 5.
    Justino, C., Duarte, A., Rocha-Santos, T.: Recent progress in biosensors for environmental monitoring: a review. Sensors 17, 2918 (2017)CrossRefGoogle Scholar
  6. 6.
    Kelly, S.D.T., Suryadevara, N.K., Mukhopadhyay, S.C.: Towards the implementation of IoT for environmental condition monitoring in homes. IEEE Sens. J. 13, 3846–3853 (2013)CrossRefGoogle Scholar
  7. 7.
    Kleinrock, L., Tobagi, F.: Packet switching in radio channels: part i - carrier sense multiple-access modes and their throughput-delay characteristics. IEEE Trans. Commun. 23, 1400–1416 (1975)CrossRefGoogle Scholar
  8. 8.
    Kong, L., Liu, X.: mZig: enabling multi-packet reception in ZigBee. In: ACM MOBICOM (2015)Google Scholar
  9. 9.
    Laufer, R., Kleinrock, L.: The capacity of wireless CSMA/CA networks. IEEE/ACM Trans. Netw. 24, 1518–1532 (2016)CrossRefGoogle Scholar
  10. 10.
    Liu, Y., Yang, C., Jiang, L., Xie, S., Zhang, Y.: Intelligent edge computing for IoT-based energy management in smart cities. IEEE Netw. 33, 111–117 (2019)CrossRefGoogle Scholar
  11. 11.
    Ronen, E., Shamir, A., Weingarten, A.O., Flynn, C.O.: IoT goes nuclear: creating a ZigBee chain reaction. In: IEEE S&P (2017)Google Scholar
  12. 12.
    Sobrinho, J.L., de Haan, R., Brazio, J.M.: Why RTS-CTS is not your ideal wireless LAN multiple access protocol. In: IEEE WCNC (2005)Google Scholar
  13. 13.
    Tobagi, F., Kleinrock, L.: Packet switching in radio channels: Part II - the hidden terminal problem in carrier sense multiple-access and the busy-tone solution. IEEE Trans. Commun. 23, 1417–1433 (1975)CrossRefGoogle Scholar
  14. 14.
    Ziouva, E., Antonakopoulos, T.: CSMA/CA performance under high traffic conditions: throughput and delay analysis. Computer Communications (2002)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Shanghai Jiao Tong UniversityShanghaiChina
  2. 2.China Electronics Technology Group CorporationBeijingChina

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