On the randomness analysis of link quality prediction: limitations and benefits

TL;DR

This paper analyzes how the inherent randomness of wireless transmission affects link quality prediction models in multi-hop networks, highlighting limitations and potential benefits for network performance.

Contribution

It provides a detailed analysis of the stochastic effects on link quality prediction models and discusses their implications for wireless multi-hop network applications.

Findings

Stochastic nature limits prediction accuracy

Randomness impacts network performance improvements

Benefits include robustness in dynamic environments

Abstract

In wireless multi-hop networks, such as wireless sensor networks, link quality (LQ) is one of the most important metrics and is widely used in higher-layer applications such as routing protocols. An accurate link quality prediction may greatly help to improve the performance of wireless multi-hop networks. Researchers have proposed a lot of link quality prediction models in recent years. However, due to the dynamic and stochastic nature of wireless transmission, the performance of link quality prediction remains challenging. In this article, we mainly analyze the influence of the stochastic nature of wireless transmission on the link quality prediction model and discuss the benefits in the application of wireless multi-hop networks with the performance-limited link quality prediction models.