Enabling Communication via Automotive Radars: An Adaptive Joint Waveform Design Approach

Large scale deployment of connected vehicles with cooperative sensing technologies increases the demand on the vehicular communication spectrum in 5.9 GHz allocated for the exchange of safety messages. To support high data rates needed by such applications, the millimeter-wave (mmWave) automotive radar spectrum at 76-81 GHz can be utilized for communication. For this purpose, joint automotive radar-communication (JARC) system designs have been proposed in the literature to perform both functions using the same waveform. However, employing a large band in the mmWave spectrum deteriorates the performance of both radar and communication functions due to frequency-selectivity. In this paper, we address the optimal joint waveform design problem for wideband JARC systems via Orthogonal Frequency-Division Multiplexing (OFDM). We show that the problem is a non-convex quadratically constrained quadratic fractional programming (QCQFP) problem, which is known to be NP-hard. Existing approaches to solve QCQFP include Semidefinite Relaxation (SDR) and randomization approaches, which have high time complexity. Instead, we propose an approximation method to solve QCQFP more efficiently by leveraging structured matrices in the quadratic fractional objective function. Finally, we evaluate the efficacy of the proposed approach through numerical results.