标题： 资源高效下一代侧向链路通信中的中继选择与用户设备接入 显示英文标题

标题： Relay Selection and User Equipment Admission in Resource-Efficient NextG Sidelink Communications

摘要： 5G/6G 侧链路通信解决了通过作为中继连接到 gNodeB 的内层用户设备（UE）来连接无法直接访问基站的外层 UE 的挑战。关键性能指标包括可实现的数据速率、能够连接到 gNodeB 的外层 UE 数量以及外层 UE 建立连接时所经历的延迟。我们考虑了基于信道、干扰和流量特性的外层 UE 到内层 UE 分配问题。我们构建了一个优化问题以最大化用户的加权总数据速率，其中权重可以表示优先级、等待时间和队列长度。此优化适应与信道和干扰特性相关的约束条件，这些特性影响链接成功传输分配流量的速率。尽管穷举搜索可以通过该非凸优化问题建立可实现速率的上限，但由于计算复杂度高导致扩展性问题，对于较大的外层 UE 数量变得不切实际。为了解决这个问题，我们提出了一种贪心算法，逐步选择链接以最大化总数据速率，并考虑已激活的链接。虽然此算法在实现高总数据速率方面有效，但可能会无意中忽略某些 UE，引发公平性问题。为缓解此问题，我们引入了一种公平性导向的算法，根据等待时间或队列长度调整权重，确保最初具有有利条件的 UE 不会随着时间推移过度损害其他 UE 的利益。我们证明，这种策略不仅提高了 UE 的平均接入比率，还确保了它们之间服务分配更加公平，从而为侧链路通信提供了一个平衡且公平的解决方案。 显示英文摘要

摘要： 5G/6G sidelink communications addresses the challenge of connecting outer UEs, which are unable to directly access a base station (gNodeB), through inner UEs that act as relays to connect to the gNodeB. The key performance indicators include the achievable rates, the number of outer UEs that can connect to a gNodeB, and the latency experienced by outer UEs in establishing connections. We consider problem of determining the assignment of outer UEs to inner UEs based on the channel, interference, and traffic characteristics. We formulate an optimization problem to maximize a weighted sum rate of UEs, where weights can represent priority, waiting time, and queue length. This optimization accommodates constraints related to channel and interference characteristics that influence the rates at which links can successfully carry assigned traffic. While an exhaustive search can establish an upper bound on achievable rates by this non-convex optimization problem, it becomes impractical for larger number of outer UEs due to scalability issues related to high computational complexity. To address this, we present a greedy algorithm that incrementally selects links to maximize the sum rate, considering already activated links. This algorithm, although effective in achieving high sum rates, may inadvertently overlook some UEs, raising concerns about fairness. To mitigate this, we introduce a fairness-oriented algorithm that adjusts weights based on waiting time or queue length, ensuring that UEs with initially favorable conditions do not unduly disadvantage others over time. We show that this strategy not only improves the average admission ratio of UEs but also ensures a more equitable distribution of service among them, thereby providing a balanced and fair solution to sidelink communications.