## 2 Related Work  
### Threshold Determination-Based Loss Differentiation  
In terms of threshold determination-based loss differentiation algorithms, the Biaz scheme [4] utilizes packet IAT to discriminate between types of packet loss. The mBiaz scheme [5] offers a tradeoff between low misclassification of congestion losses and high throughput by modifying the threshold in Biaz. The Spike scheme [6] determines link congestion by comparing the ROTT with two thresholds, while the ZigZag scheme [5] distinguishes packet loss based on the number of lost packets, mean ROTT, and deviation. [PERSON] [13] proposed an end-to-end non-congestion packet loss detection (NCPLD) algorithm that measures the sender's RTT and compares it with measured delay without congestion to determine the type of packet loss. [PERSON] et al. [14] proposed an RTT estimation method based on the ARIMA (2,1,1) model and calculated packet backlogs using estimated RTT mutations to differentiate between congestion losses and non-congestion losses. In [15], a loss differentiation method, RTT ECN loss differentiation (RELD), based on ECN signaling and RTT is proposed, taking into account the packet number of ECN tags, the number of lost packets, RTT mean, and RTT deviation. TCP-wireless environment, link losses, and congestion packet loss models (TCP-WELCOME) [16] distinguish packet loss by observing the history of RTT sample evolution on the link and the data packet loss trigger. The loss differentiation algorithm, loss recovery, and differentiation (TCP-LoRaD) [17] is modified based on the TCP-WELCOME algorithm to calculate RTT. TCP Westwood [7] relies on end-to-end bandwidth estimates to determine the cause of packet loss. The authors in [8] set different thresholds according to the amount of unconfirmed data in the network to determine the type of packet loss. Considering that link error packet loss in the network is related to packet size, and packet loss caused by congestion is independent of packet size, the authors of [18] proposed a WMPLD (Wireless Multimedia Packet Loss Discrimination) scheme. In [19], the WMPLD threshold is modified, and a WMPLD+ scheme is proposed; different simulation scenarios are designed to analyze the performance of Biaz, mBiaz, Spike, TFRC satellite, WMPLD, and WMPLD+ schemes.  
Furthermore, a loss differentiation algorithm for long-term evolution (LDA-LTE) [9] is proposed in 4G-LTE mobile networks to analyze loss patterns in congestion and link error scenarios based on parameters such as congestion level, average packet loss rate, average RTT, number of continuous losses, frequency of losses, and transmission delay jitter. Differentiation-based opportunistic linked-increases algorithm (D-OLIA) [10] identifies packet loss types by combining characteristic values of delay jitter and congestion window jitter, thus addressing the limitation of relying solely on delay or congestion window analysis. However, these methods typically require setting thresholds for the features used in their algorithms. The determination of thresholds primarily relies on experience, and establishing the relationship between multiple thresholds proves challenging, thereby impacting the accuracy of loss differentiation.