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most citedFrom Freshness to Effectiveness: Goal-Oriented Sampling for Remote Decision Making

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cs.IT20261 cited

From Freshness to Effectiveness: Goal-Oriented Sampling for Remote Decision Making

Aimin Li, Shaohua Wu, Gary C. F. Lee +1

Data freshness, measured by Age of Information (AoI), is highly relevant in networked applications such as Vehicle to Everything (V2X), smart health systems, and Industrial Interne…

cs.IT2025

Error Floor of ML-Decoded Spinal Codes in the Finite Blocklength Regime

Aimin Li, Shaohua Wu, Xiaomeng Chen +1

Spinal codes is a new family of capacity-achieving rateless codes that has been shown to achieve better rate performance compared to Raptor codes, Strider codes, and rateless Low-D…

cs.IT2025

Unified Upper Bounds on the ML decoding Error Probability of Spinal Codes over Fading Channels

Aimin Li, Xiaomeng Chen, Shaohua Wu +2

Performance evaluation of particular channel coding has been a significant topic in coding theory, often involving the use of bounding techniques. This paper focuses on the new fam…

cs.IT2024

Sampling to Achieve the Goal: An Age-aware Remote Markov Decision Process

Aimin Li, Shaohua Wu, Gary C. F. Lee +2

Age of Information (AoI) has been recognized as an important metric to measure the freshness of information. Central to this consensus is that minimizing AoI can enhance the freshn…

cs.IT2024

Optimal Sampling for Uncertainty-of-Information Minimization in a Remote Monitoring System

Xiaomeng Chen, Aimin Li, Shaohua Wu

In this paper, we study a remote monitoring system where a receiver observes a remote binary Markov source and decides whether to sample and transmit the state through a randomly d…