With the dramatic increase in the number of users and the widespread use of smartphones, most of the internet content today is provided by cellular connections. The purpose of many active queue management algorithms developed for the cellular Long-Term Evolution network is to prevent forced packet drops in the Evolved Node B (eNodeB) Radio Link Control buffer and to improve delay and end-to-end throughput values. Although the algorithms developed in the literature improve some of the end-to-end throughput, delay, and packet data fraction values during bottleneck and congestion, they cannot balance these values. The proposed virtual queue management algorithm recalculates the average queue value and the packet dropping probability according to different traffic loads to solve the queue delay and queue overflow problem providing a balance between throughput, delay, and packet data fraction. Simulation results illustrate that the proposed algorithm reduces the delay of the packets and increases fairness among users compared to the Drop-tail, Random Early Drop, Controlled Delay, Proportional Integral Controller Enhanced, and Packet Limited First In First Out Queue algorithms.

随着用户数量的急剧增加和智能手机的广泛使用，今天的大多数互联网内容都是由蜂窝连接提供的。为蜂窝长期演进网络开发的许多主动队列管理算法的目的是防止演进节点 B (eNodeB) 无线电链路控制缓冲区中的强制丢包，并提高延迟和端到端吞吐量值。尽管文献中开发的算法在瓶颈和拥塞期间改善了一些端到端吞吐量、延迟和数据包数据分数值，但它们无法平衡这些值。所提出的虚拟队列管理算法根据不同的流量负载重新计算平均队列值和丢包概率，以解决队列延迟和队列溢出问题，在吞吐量、延迟和数据包数据分数之间提供平衡。仿真结果表明，与 Drop-tail、Random Early Drop、Controlled Delay、Proportional Integral Controller Enhanced 和 Packet Limited First In First Out Queue 算法相比，该算法减少了数据包的延迟，提高了用户之间的公平性。