Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks
The proliferation of IoT using heterogeneous wireless technologies within the unlicensed spectrum has intensified cross-technology interference (CTI) in wireless local area networks (WLANs). As WLANs increasingly adopt time-triggered transmission methods to support real-time services, this interfere...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/1/428 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549355817893888 |
|---|---|
| author | Hanjin Kim Young-Jin Kim Won-Tae Kim |
| author_facet | Hanjin Kim Young-Jin Kim Won-Tae Kim |
| author_sort | Hanjin Kim |
| collection | DOAJ |
| description | The proliferation of IoT using heterogeneous wireless technologies within the unlicensed spectrum has intensified cross-technology interference (CTI) in wireless local area networks (WLANs). As WLANs increasingly adopt time-triggered transmission methods to support real-time services, this interference affects throughput, packet loss, and latency. This paper presents a CTI-aware rate adaptation framework designed to mitigate interference in WLANs without direct coordination with heterogeneous wireless devices. The framework includes a CTI identification model and CTI-aware rate selection algorithms. Leveraging short-time Fourier transform, the identification model captures the time–frequency–power characteristics of CTI signals, enabling the estimation of the average power of various heterogeneous wireless technologies employed by interfering devices. The rate selection algorithms predict CTI occurrence times and adjust the transmission rate accordingly, enhancing the performance of existing explicit and implicit interference mitigation methods. Experimental results demonstrated that the lightweight CTI identification model accurately estimated the average power of each type with an error margin of ±1.414 dBm, achieving this in under 1 ms on the target hardware. Additionally, applying the proposed framework to explicit interference mitigation enhanced goodput by 20.67%, reduced packet error rate by 2.38%, and decreased the probability of packets exceeding 1 ms latency by 0.932% compared to conventional methods. |
| format | Article |
| id | doaj-art-765d7560801448a59e8dc5a4cdb13c1d |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-765d7560801448a59e8dc5a4cdb13c1d2025-01-10T13:15:30ZengMDPI AGApplied Sciences2076-34172025-01-0115142810.3390/app15010428Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area NetworksHanjin Kim0Young-Jin Kim1Won-Tae Kim2Future Convergence Engineering Major, Department of Computer Science and Engineering, Korea University of Technology and Education, Cheonan-si 31253, Republic of KoreaIndustrial AI Research Center, Chungbuk National University, Cheongju-si 28116, Republic of KoreaFuture Convergence Engineering Major, Department of Computer Science and Engineering, Korea University of Technology and Education, Cheonan-si 31253, Republic of KoreaThe proliferation of IoT using heterogeneous wireless technologies within the unlicensed spectrum has intensified cross-technology interference (CTI) in wireless local area networks (WLANs). As WLANs increasingly adopt time-triggered transmission methods to support real-time services, this interference affects throughput, packet loss, and latency. This paper presents a CTI-aware rate adaptation framework designed to mitigate interference in WLANs without direct coordination with heterogeneous wireless devices. The framework includes a CTI identification model and CTI-aware rate selection algorithms. Leveraging short-time Fourier transform, the identification model captures the time–frequency–power characteristics of CTI signals, enabling the estimation of the average power of various heterogeneous wireless technologies employed by interfering devices. The rate selection algorithms predict CTI occurrence times and adjust the transmission rate accordingly, enhancing the performance of existing explicit and implicit interference mitigation methods. Experimental results demonstrated that the lightweight CTI identification model accurately estimated the average power of each type with an error margin of ±1.414 dBm, achieving this in under 1 ms on the target hardware. Additionally, applying the proposed framework to explicit interference mitigation enhanced goodput by 20.67%, reduced packet error rate by 2.38%, and decreased the probability of packets exceeding 1 ms latency by 0.932% compared to conventional methods.https://www.mdpi.com/2076-3417/15/1/428IoTcross-technology interferencerate adaptationWLANsBluetoothZigbee |
| spellingShingle | Hanjin Kim Young-Jin Kim Won-Tae Kim Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks Applied Sciences IoT cross-technology interference rate adaptation WLANs Bluetooth Zigbee |
| title | Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks |
| title_full | Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks |
| title_fullStr | Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks |
| title_full_unstemmed | Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks |
| title_short | Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks |
| title_sort | cross technology interference aware rate adaptation in time triggered wireless local area networks |
| topic | IoT cross-technology interference rate adaptation WLANs Bluetooth Zigbee |
| url | https://www.mdpi.com/2076-3417/15/1/428 |
| work_keys_str_mv | AT hanjinkim crosstechnologyinterferenceawarerateadaptationintimetriggeredwirelesslocalareanetworks AT youngjinkim crosstechnologyinterferenceawarerateadaptationintimetriggeredwirelesslocalareanetworks AT wontaekim crosstechnologyinterferenceawarerateadaptationintimetriggeredwirelesslocalareanetworks |