发表机构
Middle East Technical University（中东理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出自适应阈值ALOHA（SATA）分布式随机接入策略，利用1比特反馈最小化信息年龄，无需节点协调，收敛至无冲突TDMA稳态，性能优于现有ALOHA变体。
AI 中文摘要
我们提出自适应阈值ALOHA（SATA），一种用于最小化信息年龄（AoI）的分布式随机接入策略。SATA使用1比特广播反馈，不需要节点间的显式协调或消息传递。我们证明，这种最小反馈足以让每个节点完美跟踪活跃用户数量，并相应调整其接入概率。对于任何初始网络状态，只要年龄阈值满足$\Gamma \geq n$（其中$n$为网络规模），SATA在有限时间内收敛到无冲突的时分多址（TDMA）稳态。我们推导了稳态下长期平均AoI和吞吐量的闭式表达式，并证明对于$\Gamma=n$，预期瞬态持续时间按$O(n\log n)$规模增长。仿真结果证实，SATA在广泛的网络规模范围内紧密接近TDMA性能，显著优于时隙ALOHA、阈值ALOHA和1-持久阈值时隙ALOHA。值得注意的是，随着网络规模增大，SATA与基准随机接入策略之间的性能差距变得更加明显。
英文摘要
We propose Self-Adaptive Threshold ALOHA (SATA), a distributed random-access policy to minimize the Age of Information (AoI). SATA uses 1-bit broadcast feedback and requires no explicit coordination or message passing among nodes. {We show that this minimal feedback is sufficient for each node to perfectly track the number of active users and adjust its access probabilities accordingly.} For any initial network state, SATA converges to a collision-free TDMA steady state in finite time whenever the age threshold satisfies $Γ\geq n$, where $n$ is the network size. We derive closed-form expressions for the long-term average AoI and throughput in steady state, and establish that, for $Γ=n$, the expected transient duration scales as $O(n\log n)$. Simulation results confirm that SATA closely approaches TDMA performance across a wide range of network sizes, significantly outperforming Slotted ALOHA, Threshold ALOHA, and 1-persistent Threshold Slotted ALOHA. Notably, the performance gap between SATA and the benchmark random-access policies becomes more pronounced as network size grows.
Comments5 pages, 3 figures
