Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance
Abstract This article analyzes the interference issues between radar and radar, radar and communication, and communication and communication in a vehicle network equipped with a radar communication integrated system. To improve the signal-to-interference-plus-noise ratio (SINR) of radar signals whil...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-02-01
|
| Series: | EURASIP Journal on Wireless Communications and Networking |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13638-025-02432-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850067933792829440 |
|---|---|
| author | Yangshui Gao Liping Kui Qinbiao Yang Lei Xiong Rong Zhang Zhenting Chen |
| author_facet | Yangshui Gao Liping Kui Qinbiao Yang Lei Xiong Rong Zhang Zhenting Chen |
| author_sort | Yangshui Gao |
| collection | DOAJ |
| description | Abstract This article analyzes the interference issues between radar and radar, radar and communication, and communication and communication in a vehicle network equipped with a radar communication integrated system. To improve the signal-to-interference-plus-noise ratio (SINR) of radar signals while ensuring communication quality, we provide an optimized expression for the signal-to-noise ratio of radar signals constrained by communication quality. To solve mixed integer nonlinear programming optimization problems, Q-learning algorithm is introduced. In our Q-learning algorithm, based on the action state space established by transmission power and channel resources, the optimization problem is transformed into solving using a reward function. The evaluation results indicate that compared with existing solutions, the proposed algorithm can more effectively improve the total SINR of radar signals and the throughput of communication signals. |
| format | Article |
| id | doaj-art-7e89a741b3c94003a49cab697de662d6 |
| institution | DOAJ |
| issn | 1687-1499 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Wireless Communications and Networking |
| spelling | doaj-art-7e89a741b3c94003a49cab697de662d62025-08-20T02:48:11ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992025-02-012025112010.1186/s13638-025-02432-5Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication AssistanceYangshui Gao0Liping Kui1Qinbiao Yang2Lei Xiong3Rong Zhang4Zhenting Chen5School of Information Engineering, Kunming UniversitySchool of Mathematics and Computer Science, Dali UniversitySchool of Information Engineering, Kunming UniversitySchool of Information Engineering, Kunming UniversitySchool of Information Engineering, Kunming UniversitySchool of Information Engineering, Kunming UniversityAbstract This article analyzes the interference issues between radar and radar, radar and communication, and communication and communication in a vehicle network equipped with a radar communication integrated system. To improve the signal-to-interference-plus-noise ratio (SINR) of radar signals while ensuring communication quality, we provide an optimized expression for the signal-to-noise ratio of radar signals constrained by communication quality. To solve mixed integer nonlinear programming optimization problems, Q-learning algorithm is introduced. In our Q-learning algorithm, based on the action state space established by transmission power and channel resources, the optimization problem is transformed into solving using a reward function. The evaluation results indicate that compared with existing solutions, the proposed algorithm can more effectively improve the total SINR of radar signals and the throughput of communication signals.https://doi.org/10.1186/s13638-025-02432-5Interference mitigationAutomotive radarCommunicationRadar detectionReinforcement learning |
| spellingShingle | Yangshui Gao Liping Kui Qinbiao Yang Lei Xiong Rong Zhang Zhenting Chen Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance EURASIP Journal on Wireless Communications and Networking Interference mitigation Automotive radar Communication Radar detection Reinforcement learning |
| title | Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance |
| title_full | Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance |
| title_fullStr | Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance |
| title_full_unstemmed | Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance |
| title_short | Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance |
| title_sort | research on automotive radar mutual interference mitigation method based on v2x communication assistance |
| topic | Interference mitigation Automotive radar Communication Radar detection Reinforcement learning |
| url | https://doi.org/10.1186/s13638-025-02432-5 |
| work_keys_str_mv | AT yangshuigao researchonautomotiveradarmutualinterferencemitigationmethodbasedonv2xcommunicationassistance AT lipingkui researchonautomotiveradarmutualinterferencemitigationmethodbasedonv2xcommunicationassistance AT qinbiaoyang researchonautomotiveradarmutualinterferencemitigationmethodbasedonv2xcommunicationassistance AT leixiong researchonautomotiveradarmutualinterferencemitigationmethodbasedonv2xcommunicationassistance AT rongzhang researchonautomotiveradarmutualinterferencemitigationmethodbasedonv2xcommunicationassistance AT zhentingchen researchonautomotiveradarmutualinterferencemitigationmethodbasedonv2xcommunicationassistance |