Jiang Zheng-Ming, Zhang Pei-Chang, Huang Lei, He Xin, Zhang Ji-Hong, Rihan Mohamed
Guangdong Laboratory of Artificial-Intelligence and Cyber-Economics (SZ), Shenzhen University, Shenzhen 518060, China.
School of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, China.
Sensors (Basel). 2020 Feb 17;20(4):1100. doi: 10.3390/s20041100.
Due to the flourishing development of vehicle-to-vehicle (V2V) communications and autonomous driving, interference between radar sensing and communication signals becomes a challenging issue. We propose a transmit beamforming based spectrum sharing scheme to achieve peaceful coexistence between automotive multiple-input multiple-out (MIMO) radar and communication systems. Our objective is to maximize the signal-to-interference-plus-noise ratio (SINR) of the automotive radar receiver subject to the communication capacity and the transmitted power budget constraints to optimize both the communication covariance matrix and the radar transmit precoder. The formulated optimization problem is non-convex, which is converted to convex by introducing a new slack variable and then solving it using the block coordinate descent, also called alternation optimization, approach. Additionally, the ellipsoid sub-gradient method is then employed to reduce the computational complexity. Simulation results demonstrate that our proposed scheme outperforms the conventional schemes.
由于车对车（V2V）通信和自动驾驶的蓬勃发展，雷达传感与通信信号之间的干扰成为一个具有挑战性的问题。我们提出一种基于发射波束成形的频谱共享方案，以实现汽车多输入多输出（MIMO）雷达与通信系统之间的和平共存。我们的目标是在通信容量和发射功率预算约束下，最大化汽车雷达接收器的信干噪比（SINR），以优化通信协方差矩阵和雷达发射预编码器。所制定的优化问题是非凸的，通过引入一个新的松弛变量将其转化为凸问题，然后使用块坐标下降法（也称为交替优化法）来求解。此外，随后采用椭球次梯度法来降低计算复杂度。仿真结果表明，我们提出的方案优于传统方案。
