无需测量信道状态，通过位置速度预测速率，实现毫米波车联网的快速用户关联。
Contextual Bandits with Non-Stationary Correlated Rewards for User Association in MmWave Vehicular Networks
- 基于车辆位置与速度预测传输速率，构建上下文相关置信上界算法。
- 在无完美信道信息下，网络吞吐量达到基准算法的100%-103%。
- 适合高速移动场景下的低延迟车联网系统部署。
毫米波（mmWave）通信已成为车载通信的关键技术。由于毫米波车载信道快速衰落，用户关联决策通常依赖及时的车-基站（BS）间信道信息，但获取该信息极具挑战。本文仅依赖传输速率学习，提出一种低复杂度半分布式上下文相关置信上界（SD-CC-UCB）算法，无需显式测量信道状态信息（CSI），即可建立实时用户关联。在上下文多臂老虎机框架下，该算法利用车辆位置与速度预测传输速率，充分捕捉复杂信道条件以实现快速关联。同时，通过利用不同位置间传输速率的关联分布，高效筛选出可能提供最优速率的候选基站集合。为进一步优化候选基站链路的速率学习，各车辆结合干扰与切换开销，采用汤普森采样算法进行精调。数值结果表明，所提算法在无完美瞬时CSI条件下，网络吞吐量可达基准算法的100%-103%，验证了其在车载通信中的有效性。
原文摘要 · Abstract (English)
Millimeter wave (mmWave) communication has emerged as a propelling technology in vehicular communication. Usually, an appropriate decision on user association requires timely channel information between vehicles and base stations (BSs), which is challenging given a fast-fading mmWave vehicular channel. In this paper, relying solely on learning transmission rate, we propose a low-complexity semi-distributed contextual correlated upper confidence bound (SD-CC-UCB) algorithm to establish an up-to-date user association without explicit measurement of channel state information (CSI). Under a contextual multi-arm bandits framework, SD-CC-UCB learns and predicts the transmission rate given the location and velocity of the vehicle, which can adequately capture the intricate channel condition for a prompt decision on user association. Further, SD-CC-UCB efficiently identifies the set of candidate BSs which probably support supreme transmission rate by leveraging the correlated distributions of transmission rates on different locations. To further refine the learning transmission rate over the link to candidate BSs, each vehicle deploys the Thompson Sampling algorithm by taking the interference among vehicles and handover overhead into consideration. Numerical results show that our proposed algorithm achieves the network throughput within 100%-103% of a benchmark algorithm which requires perfect instantaneous CSI, demonstrating the effectiveness of SD-CC-UCB in vehicular communications.
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