Project Description:

Aerial acoustic communication attracts substantial attention for its simplicity and cost-effectiveness. Unfortunately, the preferred inaudible transmission has to strike a balance between the transmission rate and communication range, when the Bit-Error-Rate (BER) is under a certain threshold. Additionally, the performance of previous proposals can be deteriorated by dynamic channel conditions including near-far problem, device heterogeneity, and multipath fading. To this end, we propose a High-speed, long-range, and Robust Chirp Spread Spectrum (HRCSS) scheme for inaudible aerial acoustic communication under dynamic channels. HRCSS innovates in the definition of a loose orthogonality condition, and it leverages this orthogonality to overlap multiple chirp carriers in a single time duration to form a data symbol representing multiple bits, thereby substantially promoting the data rate. To further enhance system robustness in long communication ranges and dynamic channel conditions, we construct a lightweight rate adaptation algorithm and design a simple yet efficient normalization method. Experiment results reveal that HRCSS achieves a significant improvement in data rate over existing methods: it delivers 500 bps data rate with a BER of 0.24 percent at 10 m, and achieves 125 bps with zero BER at 20 m. Meanwhile, HRCSS can work adaptively under dynamic channel conditions while still retaining a BER below 3 percent.

Acknowledgement:

• For more information please visit our git repository

  People:

  • Mr. Hengling Pu (Master Student, Electrical and Electronic Engineering) - Michigan State University
  • Dr. Chao Cai (Associate Proffessor, College of Life Science & Engineering) - Huazhong University of Science and Technology

  Related Publications:

• [1] C. Cai, Z. Chen, J. Luo, H. Pu, M. Hu and R. Zheng, "Boosting Chirp Signal Based Aerial Acoustic Communication Under Dynamic Channel Conditions," in IEEE Transactions on Mobile Computing, vol. 21, no. 9, pp. 3110-3121, 1 Sept. 2022
• [2] C. Cai, R. Zheng and J. Luo, "Ubiquitous Acoustic Sensing on Commodity IoT Devices: A Survey," in IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp. 432-454, Firstquarter 2022.
• [3] C. Cai, R. Zheng, J. Li, L. Zhu, H. Pu, and M. Hu, "Asynchronous Acoustic Localization and Tracking for Mobile Targets," in IEEE Internet of Things Journal, vol. 7, no. 2, pp. 830-845, Feb. 2020.