基于目标导向的不规则重复时隙ALOHA的价值驱动大规模接入
Value-Based Massive Access through Goal-Oriented Irregular Repetition Slotted ALOHA
- University of Padova（帕多瓦大学）
- German Aerospace Center (DLR)（德国航空航天中心）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出GO-IRSA方案，结合随机接入与信念策略，实现大规模设备的目标导向通信，显著降低分布式维纳过程估计误差，并具备鲁棒性。
AI中文摘要：
目标导向的通信范式有望通过减轻通信网络的负担，同时仍传递与任务相关的信息，来支持新型实时应用。然而，迄今为止的努力主要集中在编码问题上，而介质访问方案的设计仍处于早期发展阶段，尤其是在需要为大量设备（例如用于远程监控）提供连接的情况下。在这方面，现有的目标导向方法通常是集中式的或基于简化的底层机制，需要不切实际的假设。在这项工作中，我们提出了目标导向的不规则重复时隙ALOHA（GO-IRSA）方案，该方案将现代随机接入技术与基于信念的策略相结合。GO-IRSA不会给传感器带来显著的计算负担，也不需要频繁的反馈，并且在拥有数千个传感器的网络中，相对于最优集中式解决方案，它可以将分布式维纳过程估计的平均误差和最坏情况误差降低超过30%，并且对不完美的干扰消除和不准确的过程知识具有鲁棒性。
英文摘要：
The goal-oriented communication paradigm is poised to enable novel real-time applications by easing the burden on communication networks while still delivering task-relevant information. However, efforts so far have focused on the encoding problem, while the design of medium access schemes is still in the early stages of development, especially when connectivity is to be provided to a massive number of devices, e.g., for remote monitoring. In this respect, existing goal-oriented approaches are often centralized or based on simplified underlying mechanisms, requiring unrealistic assumptions. In this work, we present the Goal-oriented Irregular Repetition Slotted ALOHA (GO-IRSA) scheme, which combines modern random access techniques with belief-based policies. GO-IRSA does not impose significant computing loads on the sensors or require frequent feedback, and it can reduce the average and worst-case error of the estimate of a distributed Wiener process by over 30% with respect to the optimal centralized solution in a network with thousands of sensors, and is robust to imperfect interference cancellation and inaccurate process knowledge.
