With the widespread application of millimeter-wave (mmWave) radar technology in modern vehicles, vehicle-to-vehicle radar interference becomes a significant concern in exploiting the benefits of mmWave radar. This letter studies the radar mutual interference among vehicles on a practical bi-directional multi-lane road. Particularly, the fluctuation of the target radar cross-section (RCS) is modeled by Swerling I model and Chi-square model. Closed-form expression for successful ranging probability that works as the radar ranging performance metric is obtained by applying the stochastic geometry. Compared with constant RCS model in previous literature, the proposed performance metric based on random RCS models can provide more precise and intuitive results. The simulation results show that the increasing ranging distance and intensity of vehicles lead to a sharp decrease of the successful ranging probability.

The joint communication-radar system (JCRS) is promising in the future wireless network which can provide great advantages, such as structure simplification, interference mitigation and less resource occupation, compared with the traditional separate deployment of communication and radar systems. However, with the large number of users accessing the network both for communication and radar purposes, massive user data packets may arrive at the base station equipped with the JCRS in a short period of time, which can easily cause the backlog of user data packets and affect network stability. To solve this problem, we introduce orthogonal frequency division multiple access (OFDMA) technique into the JCRS to support communication function for massive users. Then, we design a queue scheduling model of user data packets to perceive the status of current queue backlog and schedule the queue dynamically. Different from the existing works, we formulate a transmit power minimization problem, while taking network stability and radar detection performance into account. Since the problem is a non-convex problem, we transform it into the upper-bound minimization of drift-plus-function by using the Lyapunov optimization technique. Further, the successive convex approximation method and parameter transformation method are exploited to convert this problem into a convex problem. Finally, we derive an optimal closed-form power allocation expression by using the Lagrangian dual decomposition method and propose a dynamic subcarrier and power allocation algorithm. Simulation results show that the proposed algorithm can achieve an [O(1/?),O(?)] power-backlog tradeoff and demonstrate the efficacy of the proposed algorithm in reducing transmit power while significantly enhancing network stability.

Roadside units (RSUs) can help vehicles sense the traffic environment, so as to improve traffic safety. Since the sensing capability of single RSU is limited, we propose a multiple RSUs cooperative radar sensing network (RSU-CRSN) with signal-level fusion technique. Spatial registration is an essential prerequisite and foundation for RSU-CRSN with signal-level fusion. In this paper, we present an adjustable beam enabled spatial registration algorithm (AB-SRA) that makes the sensing area of each RSU coincide by adjusting the sensing beam width of RSU. To adjust the width of sensing beam flexibly, a beamwidth adjustable beamforming algorithm (BABA) is proposed in this paper. Simulation results show that the performance of AB-SRA is close to perfect spatial registration.