Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance

(2025) 2025:6 Gao et al. J Wireless Com Network https://doi.org/10.1186/s13638-025-02432-5 RESEARCH EURASIP Journal on Wireless Communications and Networking Open Access Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance Yangshui Gao1* , Liping Kui2†, Qinbiao Yang1†, Lei Xiong1†, Rong Zhang1† and Zhenting Chen1† † Liping Kui, Qinbiao Yang, Lei Xiong, Rong Zhang, and Zhenting Chen contributed equally to this work. *Correspondence: 1 School of Information Engineering, Kunming University, No.2 Puxin Road, Kunming 650214, Yunnan, China 2 School of Mathematics and Computer Science, Dali University, No.2 Hongsheng Road, Dali 671003, Yunnan, China 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-interferenceplus-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. Keywords: Interference mitigation, Automotive radar, Communication, Radar detection, Reinforcement learning 1 Introduction With the development of artificial intelligence, computer and electronic technology, automated driving vehicles (ADV) is becoming a reality. As an important component of ADV, with the help of advanced driver assistance system (ADAS), ADV can effectively prevent traffic accidents, which is predicted to prevent more than 85 percent of traffic accidents [1–3]. Traffic jam can be also effectively solved by ADAS. In the future, more and more vehicles will be installed with ADAS. Automobile radar is widely used in ADAS to provide real-time ambient information to vehicles. By detecting information related to distance, speed, and angle, safety functions such as adaptive cruise control and automatic emergency braking can be achieved. Compared with video and laser radar, the advantage of automobile radar is that it can work stably under bad weather conditions. In addition, vehicular communication can receive packets from other vehicles to obtain situational awareness, thus vehicular communication is also a key component of ADAS [4, 5]. © The Author(s) 2025. 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To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. Gao et al. J Wireless Com Network (2025) 2025:6 Currently, there is relatively little research on radar communication integration technology in the field of vehicle networking, while there are many studies on this aspect in other wireless network fields. Next, we will first introduce the radar communication integration technology of other wireless networks, and then introduce the that of ADV. In other wireless network fields, research on radar communication integration technology can be divided into two categories: radar and communication beam sharing and non-sharing. In the research of beam non-sharing technology, the work in [6] is to study how to use projection technology to achieve the coexistence of radar and cellular base station (BS) communication systems. Subsequently, the authors in [7] propose using adaptive signal processing method to achieve the coexistence of radar and communication. The work in [8, 9] researches on using interference alignment technology in Multiple-Input Multiple-Output (MIMO) communication systems to solve the mutual interference problem when phased array radar and communication systems coexist. In the research of beam sharing technology, the works in [10, 11] explore the mechanism of sharing beams between communication and radar in the architecture of mobile sensor networks. The work in [12] is based on the radar communication integration system, designing globally optimal omnidirectional and directional beam patterns. The authors in [13–15] study adaptive fast beamforming technology in millimeter wave (MMWave) radar communication systems. However, it is still an unresolved problem that how the radar system can benefit from the communication system. The authors in [16] study the radar communication integration technology of 60 GHz millimeter wave, where communication and radar signals share the same millimeter wave beam. The authors in [16] further study the use of spread spectrum orthogonal technology to reduce signal interference in integrated communication radar network [17]. The work in [18] investigates the design of the optimal beamformer in a radar communication joint system using millimeter waves. In the field of ADV, so far, there is still little work on communication radar integration technology. The works in [19–22] are a few papers on the research of radar-communication integrated technology. The work in [19] proposes a centralized integrated architecture for automotive communication radar, which relies on vehicle to everything (V2X) communication to allocate spectrum resources for automotive radar in order to reduce interference between radar signals. The authors in [20] analyze the mutual interference between the frequency modulated continuous wave (FMCW) radar and the communication system from the perspective of occurrence probability and impact, and introduce a distributed networking protocol called RadChat, which alleviates the interference between the FMCW-based automotive radars through the cooperation of radar and communication, including self-interference. To address the serious interference and insufficient (...truncated)