Automotive Radar Optimization Design in a Spectrally Crowded V2I Communication Environment

A main challenge for radar-aided millimeter wave (mmWave) vehicle-to-infrastructure (V2I) communication application, is that it requires mitigating the mutual interference between vehicular radar and communication operating at same frequency bands. This paper considers the joint design of the multiple-input multiple-output (MIMO) transmit waveform and receive filter bank for road side unit (RSU)-mounted radar in a spectrally crowded V2I communication environment. With the criterion of maximizing the average signal-to-interference-plus-noise ratio (SINR), a non-convex problem, which involves the weighted-sum waveform energy over the overlayed space-frequency bands, energy and similarity constraints, is formulated. An iterative algorithm is proposed to solve the joint optimization problem. At each iteration, the transmit waveform is optimized based on the alternating direction method of multipliers (ADMM) method with a significantly lower computational complexity. As a consequence, accurate location information derived from the optimized radar is used to reduce the beam training overhead of V2I communication links. Finally, simulation results display the effectiveness of the devised method in finding feasible and enhanced solutions, importantly outperforming several counterparts.