论文标题
有效的车辆互联网速率降低多重访问：联合边缘学习和延迟最小化
Efficient Rate-Splitting Multiple Access for the Internet of Vehicles: Federated Edge Learning and Latency Minimization
论文作者
论文摘要
速率分类的多个访问（RSMA）最近在多Antenna辅助的无线下行链路中受到了青睐，这是为了放松发射机（CSIT）的通道状态信息的准确性，同时实现高光谱效率并提供安全保证。这些好处在高速车辆排行管中尤为重要，因为它们的高多普勒会影响CSIT的估计准确性。为了应对这一挑战，我们提出了一个基于RSMA的车辆互联网（IOV）解决方案，该解决方案共同考虑了下行链路中的排队控制和联合边缘学习（FEES）。具体而言，所提出的框架旨在在IOV排内传输单播控制消息，以及保留隐私的感觉辅助下行链路非正交单播和多播（NOUM）。鉴于这个复杂的框架，制定了一个多目标优化问题，以最大程度地减少感觉下行链路的延迟和排在排内的车辆的偏差。为了有效解决此问题，开发了一个块坐标下降（BCD）框架，以将主要的多目标问题分解为两个子问题。然后，为了求解这些非凸子问题，开发了连续的凸近似（SCA）和模型预测控制方法（MPC）方法，分别用于解决基于感觉的基于感觉的下行链路问题和排控制问题。我们的仿真结果表明，提出的基于RSMA的IOV系统的表现优于常规系统。
Rate-Splitting Multiple Access (RSMA) has recently found favour in the multi-antenna-aided wireless downlink, as a benefit of relaxing the accuracy of Channel State Information at the Transmitter (CSIT), while in achieving high spectral efficiency and providing security guarantees. These benefits are particularly important in high-velocity vehicular platoons since their high Doppler affects the estimation accuracy of the CSIT. To tackle this challenge, we propose an RSMA-based Internet of Vehicles (IoV) solution that jointly considers platoon control and FEderated Edge Learning (FEEL) in the downlink. Specifically, the proposed framework is designed for transmitting the unicast control messages within the IoV platoon, as well as for privacy-preserving FEEL-aided downlink Non-Orthogonal Unicasting and Multicasting (NOUM). Given this sophisticated framework, a multi-objective optimization problem is formulated to minimize both the latency of the FEEL downlink and the deviation of the vehicles within the platoon. To efficiently solve this problem, a Block Coordinate Descent (BCD) framework is developed for decoupling the main multi-objective problem into two sub-problems. Then, for solving these non-convex sub-problems, a Successive Convex Approximation (SCA) and Model Predictive Control (MPC) method is developed for solving the FEEL-based downlink problem and platoon control problem, respectively. Our simulation results show that the proposed RSMA-based IoV system outperforms the conventional systems.
