Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
167 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

NNCTC: Physical Layer Cross-Technology Communication via Neural Networks (2403.10014v1)

Published 15 Mar 2024 in cs.NI and cs.AI

Abstract: Cross-technology communication(CTC) enables seamless interactions between diverse wireless technologies. Most existing work is based on reversing the transmission path to identify the appropriate payload to generate the waveform that the target devices can recognize. However, this method suffers from many limitations, including dependency on specific technologies and the necessity for intricate algorithms to mitigate distortion. In this work, we present NNCTC, a Neural-Network-based Cross-Technology Communication framework inspired by the adaptability of trainable neural models in wireless communications. By converting signal processing components within the CTC pipeline into neural models, the NNCTC is designed for end-to-end training without requiring labeled data. This enables the NNCTC system to autonomously derive the optimal CTC payload, which significantly eases the development complexity and showcases the scalability potential for various CTC links. Particularly, we construct a CTC system from Wi-Fi to ZigBee. The NNCTC system outperforms the well-recognized WEBee and WIDE design in error performance, achieving an average packet reception rate(PRR) of 92.3% and an average symbol error rate(SER) as low as 1.3%.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (46)
  1. Kameswari Chebrolu and Ashutosh Dhekne. 2012. Esense: Energy sensing-based cross-technology communication. IEEE Transactions on Mobile Computing 12, 11 (2012), 2303–2316.
  2. TwinBee: Reliable physical-layer cross-technology communication with symbol-level coding. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications. IEEE, 153–161.
  3. WibZig: Reliable and Commodity-device Compatible PHY-CTC via Chip Emulation in Phase. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks. 191–204.
  4. DDSP: Differentiable digital signal processing. arXiv preprint arXiv:2001.04643 (2020).
  5. Time Synchronization based on Cross-Technology Communication for IoT Networks. IEEE Internet of Things Journal (2023).
  6. Spectrum efficient communication for heterogeneous IoT networks. IEEE Transactions on Network Science and Engineering 9, 6 (2022), 3945–3955.
  7. ComNet: Combination of deep learning and expert knowledge in OFDM receivers. IEEE Communications Letters 22, 12 (2018), 2627–2630.
  8. Wi-Lo: Emulation of LoRa using Commodity 802.11 b WiFi Devices. In ICC 2022-IEEE International Conference on Communications. IEEE, 4414–4419.
  9. Andrea Goldsmith. 2005. Wireless communications. Cambridge university press.
  10. WIDE: Physical-level CTC via digital emulation. In Proceedings of the 18th International Conference on Information Processing in Sensor Networks. 49–60.
  11. Zigfi: Harnessing channel state information for cross-technology communication. IEEE/ACM Transactions on Networking 28, 1 (2020), 301–311.
  12. Model-driven deep learning for physical layer communications. IEEE Wireless Communications 26, 5 (2019), 77–83.
  13. Sionna: An open-source library for next-generation physical layer research. arXiv preprint arXiv:2203.11854 (2022).
  14. Achieving receiver-side cross-technology communication with cross-decoding. In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking. 639–652.
  15. Song Min Kim and Tian He. 2015. Freebee: Cross-technology communication via free side-channel. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. 317–330.
  16. Physical-layer cross-technology communication with narrow-band decoding. In 2019 IEEE 27th International Conference on Network Protocols (ICNP). IEEE, 1–2.
  17. WiBle: Physical-layer cross-technology communication with symbol transition mapping. In 2021 18th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). IEEE, 1–9.
  18. Zhijun Li and Yongrui Chen. 2020a. BLE2LoRa: Cross-technology communication from bluetooth to LoRa via chirp emulation. In 2020 17th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). IEEE, 1–9.
  19. Zhijun Li and Yongrui Chen. 2020b. Bluefi: Physical-layer cross-technology communication from bluetooth to wifi. In 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS). IEEE, 399–409.
  20. Zhijun Li and Tian He. 2017. Webee: Physical-layer cross-technology communication via emulation. In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking. 2–14.
  21. Zhijun Li and Tian He. 2018. LongBee: Enabling long-range cross-technology communication. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications. IEEE, 162–170.
  22. XiTuXi: Sealing the Gaps in Cross-Technology Communication by Neural Machine Translation. In The 21st ACM Conference on Embedded Networked Sensor Systems (SenSys ’23). ACM, Istanbul, Turkiye, 13. https://doi.org/10.1145/3625687.3625802
  23. LTE2B: Time-domain cross-technology emulation under LTE constraints. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems. 179–191.
  24. Xfi: Cross-technology iot data collection via commodity wifi. In 2020 IEEE 28th International Conference on Network Protocols (ICNP). IEEE, 1–11.
  25. WiBeacon: Expanding BLE location-based services via WiFi. In Proceedings of the 27th annual international conference on mobile computing and networking. 83–96.
  26. Performance evaluation of channel decoding with deep neural networks. In 2018 IEEE International Conference on Communications (ICC). IEEE, 1–6.
  27. An end-to-end block autoencoder for physical layer based on neural networks. arXiv preprint arXiv:1906.06563 (2019).
  28. Timothy O’shea and Jakob Hoydis. 2017. An introduction to deep learning for the physical layer. IEEE Transactions on Cognitive Communications and Networking 3, 4 (2017), 563–575.
  29. John G Proakis. 2008. Digital communications. McGraw-Hill, Higher Education.
  30. Next-generation IoT devices: Sustainable eco-friendly manufacturing, energy harvesting, and wireless connectivity. IEEE Journal of Microwaves 3, 1 (2023), 237–255.
  31. LoRaBee: Cross-technology communication from LoRa to ZigBee via payload encoding. In 2019 IEEE 27th International Conference on Network Protocols (ICNP). IEEE, 1–11.
  32. Autoencoder-based optical wireless communications systems. In 2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 1–6.
  33. Neural network-based OFDM receiver for resource constrained IoT devices. IEEE Internet of Things Magazine 5, 3 (2022), 158–164.
  34. Demo Abstract: Using Neural Networks as Modulators for IoT Gateways. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks. 372–373.
  35. Symbol-level cross-technology communication via payload encoding. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS). IEEE, 500–510.
  36. LigBee: Symbol-Level Cross-Technology Communication from LoRa to ZigBee. In IEEE INFOCOM 2023-IEEE Conference on Computer Communications. IEEE, 1–10.
  37. Deep learning for massive MIMO CSI feedback. IEEE Wireless Communications Letters 7, 5 (2018), 748–751.
  38. Yu-chen Wu and Jun-wen Feng. 2018. Development and application of artificial neural network. Wireless Personal Communications 102 (2018), 1645–1656.
  39. Parallel Cross-technology Transmission from IEEE 802.11 ax to Heterogeneous IoT Devices. In IEEE INFOCOM 2023-IEEE Conference on Computer Communications. IEEE, 1–10.
  40. c-Chirp: Towards symmetric cross-technology communication over asymmetric channels. IEEE/ACM Transactions on Networking 29, 3 (2021), 1169–1182.
  41. WiRa: Enabling cross-technology communication from WiFi to LoRa with IEEE 802.11 ax. In IEEE INFOCOM 2022-IEEE Conference on Computer Communications. IEEE, 430–439.
  42. C-morse: Cross-technology communication with transparent morse coding. In IEEE INFOCOM 2017-IEEE Conference on Computer Communications. IEEE, 1–9.
  43. Explicit channel coordination via cross-technology communication. In Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services. 178–190.
  44. DeepWiPHY: Deep learning-based receiver design and dataset for IEEE 802.11 ax systems. IEEE Transactions on Wireless Communications 20, 3 (2020), 1596–1611.
  45. Deep-waveform: A learned OFDM receiver based on deep complex-valued convolutional networks. IEEE Journal on Selected Areas in Communications 39, 8 (2021), 2407–2420.
  46. Stripcomm: Interference-resilient cross-technology communication in coexisting environments. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications. IEEE, 171–179.

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now