Efficient Compressed Sensing-Driven Wireless Multi-Hop Seismic Data Transmission Network

In recent years, the advancement of cableless seismic data acquisition devices, particularly nodal seismographs, has revolutionized seismic exploration. However, traditional "blind acquisition" methods face significant limitations, including the inability to enable real-time monitoring, challenges in ensuring data transmission stability, and the inefficiency of device retrieval in large-scale exploration projects. To address these issues, this paper proposes an Efficient Com-pressed Sensing-Driven Wireless Multi-Hop Seismic Data Transmission Network (WMDTN), which inte-grates a hierarchical wireless multi-hop network (HWMN) and compressed sensing (CS) technology to optimize data transmission and reduce the volume of seismic data. The network architecture comprises a core network based on LTE for long-range communication and a multi-hop network utilizing Wi-Fi for short-range, high-density data transmission. The system employs advanced hardware components, including high-resolution ADCs, FPGA-based controllers, and dual-frequency GPS modules, to ensure precise data acquisition and synchronization. Furthermore, the pro-posed CS-based transmission method significantly enhances channel capacity by compressing seismic data while maintaining signal integrity, as evidenced by a 14 dB SNR at a 32% compression ratio. Experimental results demonstrate the network's robustness, with an average transmission rate of 1.161 MB/s in the core network and 0.459 MB/s in multi-hop networks, mak-ing it highly suitable for large-scale, real-time seismic exploration applications.

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Publication Details

Journal
Journal of Computer Science and Artificial Intelligence
Published
2025-03-27
DOI
https://doi.org/10.54097/fcan0a87
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
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article

Efficient Compressed Sensing-Driven Wireless Multi-Hop Seismic Data Transmission Network

Tongyu Nie, Xunqian Tong, Yuqi Wang
Journal of Computer Science and Artificial Intelligence
Underwater Vehicles and Communication Systems
article

Efficient Compressed Sensing-Driven Wireless Multi-Hop Seismic Data Transmission Network

Tongyu Nie, Xunqian Tong, Yuqi Wang
article en

Abstract

In recent years, the advancement of cableless seismic data acquisition devices, particularly nodal seismographs, has revolutionized seismic exploration. However, traditional "blind acquisition" methods face significant limitations, including the inability to enable real-time monitoring, challenges in ensuring data transmission stability, and the inefficiency of device retrieval in large-scale exploration projects. To address these issues, this paper proposes an Efficient Com-pressed Sensing-Driven Wireless Multi-Hop Seismic Data Transmission Network (WMDTN), which inte-grates a hierarchical wireless multi-hop network (HWMN) and compressed sensing (CS) technology to optimize data transmission and reduce the volume of seismic data. The network architecture comprises a core network based on LTE for long-range communication and a multi-hop network utilizing Wi-Fi for short-range, high-density data transmission. The system employs advanced hardware components, including high-resolution ADCs, FPGA-based controllers, and dual-frequency GPS modules, to ensure precise data acquisition and synchronization. Furthermore, the pro-posed CS-based transmission method significantly enhances channel capacity by compressing seismic data while maintaining signal integrity, as evidenced by a 14 dB SNR at a 32% compression ratio. Experimental results demonstrate the network's robustness, with an average transmission rate of 1.161 MB/s in the core network and 0.459 MB/s in multi-hop networks, mak-ing it highly suitable for large-scale, real-time seismic exploration applications.

Journal of Computer Science and Artificial IntelligenceVol. 2(3)
Openalex Percentile: Top 92%
Underwater Vehicles and Communication Systems
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