Anti-Interference Technology of Broadband and Narrowband Wireless Network for Symbiotic IoT Sensing Devices of Digital Converter Station
As the construction of the new power system progresses, it has become increasingly evident that a change in the production model driven by digital technology is an inevitable choice to promote the high-quality development of the power grid. The interconnection and interoperability of multiple IoT sensing devices for digital converter stations are achieved through the utilisation of broadband and narrowband communication technologies, meeting diverse needs such as real-time monitoring and data collection. However, with the increase in the number of sensing devices and the adoption of integrated broadband and narrowband networks, the issue of co-channel interference (CCI) due to spectrum scarcity has become increasingly prominent.To enhance the utilisation efficiency of spectrum resources and communication reliability, and to establish a novel digital power system based on Symbiotic Internet of Things (Symbiotic IoT), this paper investigates anti-interference optimisation methods leveraging Non-Orthogonal Multiple Access (NOMA) technology. For broadband and narrowband wireless networks applied to the IoT sensing devices in digital converter stations, the access point (AP) selection and power allocation strategies of the sensing devices are modeled as an optimisation problem. An AP-UE association algorithm is proposed to achieve optimal matching between sensing devices and access points. On this basis, to address the issue of CCI, a power allocation algorithm based on Deep Deterministic Policy Gradient (DDPG) is proposed to enable efficient power allocation. This further enhances the anti-interference capability of the Symbiotic IoT network within the converter station, ensuring reliable communication among Symbiotic IoT devices to achieve efficient collaboration and intelligent interaction.
Authors
- Zhuojun Duan
- Cong Yu (ORCID: https://orcid.org/0000-0001-6744-021X)
- Yang Lu
- Donglei Zhang (ORCID: https://orcid.org/0000-0002-3704-2971)
Institutions
- North China Electric Power University (CN)
- China Power Engineering Consulting Group (China) (CN)
- China Electric Power Research Institute
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1109/jiot.2025.3575855
- Primary Topic
- Wireless Sensor Networks and IoT
- Type
- article
- Field-Weighted Citation Impact
- 0.00