Optical camera communication (OCC) has emerged as a key enabling technology for the seamless operation of future autonomous vehicles. By leveraging the supreme performance of OCC, we can meet the stringent requirements of ultra-reliable and low-latency communication (uRLLC) in vehicular OCC. In this paper, we introduce a rate optimization approach in vehicular OCC through optimal power allocation while respecting uRLLC requirements. We first formulate a discrete-rate optimization problem as a mixed-integer programming (MIP) subject to average transmit power and uRLLC constraints for a given set of modulation schemes. To reduce the complexity in solving the MIP problem, we convert the discrete-rate problem into a continuous-rate optimization scheme. Then, we present an algorithm based on Lagrangian relaxation and Bisection method to solve the optimization problem. Considering the proposed algorithm, we drive the rate optimization and power allocation scheme for both discrete-rate and continuous-rate optimization schemes while satisfying uRLLC constraints. We first analyze the performance of the proposed system model through simulations. We then investigate the impact of proposed power allocation and rate optimization schemes on average rate and latency for different target bit error rates. The results show that increasing the transmit power allocation improves the average rate and latency performance.
翻译:光学摄影机通信(OCC)已成为未来自主车辆无缝运行的关键赋能技术。通过利用OCC的最高性能,我们可以满足车辆 OCC 中超可靠和低纬度通信(URLLC)的严格要求。在本文中,我们通过优化电力配置,在车辆 OCC 中引入了节率优化方法,同时尊重 URLLC 的要求。我们首先将离散节率优化方案作为混合整流程序程序(MIP)来设计一个离散节率优化问题,但需视平均传输动力和对特定调制计划的URLLLC限制情况而定。为了降低解决MIP问题的复杂性,我们将离散节率问题转换为持续速率优化计划。然后,我们根据Lagrangeian 放松和分解法提出一种算法,以解决优化问题。考虑到拟议的算法,我们推动离节率和连续节率优化计划(MILC)的节率优化和分流率计划,同时满足URLLC的制约。我们首先通过模拟分析拟议系统模型的性能性能表现。我们先通过降低解决解决离节率问题的复杂性,然后将离节率问题,我们将离节率问题转换为持续节率问题,然后将离节率问题转化为平均分配率问题,我们调查平均分配率分配率分配计划的影响。我们然后调查平均利率分配率分配率和平均分配率计划,然后调查平均分配率计划。我们,然后调查平均分配率计划,然后调查平均利率分配率分配率计划。我们,然后调查平均分差率分配率计划,然后调查平均利率分配率计划,然后调查平均利率分配率计划。我们提高率计划。