5 papers
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…
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…
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…
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…
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…